Specificity and evolution of bacterial two-component
signal transduction systems
by
Emily Jordan Capra
A.B. Molecular Biology
Princeton University, Princeton, New Jersey, 2008
SUBMITTED TO THE DEPARTMENT OF BIOLOGY IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY IN BIOLOGY
AT THE
A'S'SA""'
s~ t 4
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
SEPTEMBER 2013
©2013 Emily Jordan Capra. All rights reserved.
The author hereby grants MIT permission to reproduce and distribute publicly
paper and electronic copies of this thesis document in whole or in part in any medium
now known or hereafter created.
Signature of Author:
71
/
Emily Jordan Capra
Department of Biology
April 29, 2013
Certified by:
" Michael T. Laub
Associate Professor of Biology
Thesis supervisor
Accepted by:
AmRE Keating
Associate Professor of Biology
W I
Specificity and evolution of bacterial two-component
signal transduction systems
by
Emily J. Capra
Submitted to the Department of Biology
on April 29, 2013 in partial fulfillment of the requirements for the degree of
Doctor of Philosophy in Biology at the Massachusetts Institute of Technology
ABSTRACT
Cells possess a remarkable capacity to sense and process a diverse range of signals.
Duplication and divergence of a relatively small number of gene families has provided
the raw material enabling cells to quickly increase their signaling capacity. After
duplication, however, all pathway components are identical in sequence and function. To
evolve a new role, the pathways must become insulated at the level of signal
transduction. Two-component signal transduction systems, consisting of a sensor
histidine kinase and a cognate response regulator, are the main means by which bacteria
sense and respond to their environment. These systems have undergone extensive
duplication and lateral gene transfer such that most species encode dozens to hundreds of
these pathways, yet there is little evidence of cross-talk at the level of signal transduction.
Previous work has shown that interaction specificity is dictated by molecular recognition
and determined by a small set of specificity residues.
I begin by studying the evolutionary trajectories of specificity residues in a duplicated
two-component system that lead to insulation of pathways while at the same time
maintaining interaction between cognate kinases and regulators. I then examine
specificity residues in orthologs of a single two-component system and show that
specificity residues are typically under purifying selection, but, as a result of additions to
the two-component signaling network, can undergo bursts of diversification followed by
extended stasis. By reversing these mutations I demonstrate that avoidance of cross-talk
is a major selective pressure. Finally, I show that covalent attachment of the response
regulator to a kinase represents an alternative mechanism for enforcing specificity. In
these cases, no changes are needed to accommodate a duplication; the high effective
concentration of the covalently attached response regulator prevents cross-talk with other
two component proteins in the cell. This may allow hybrid kinases to be duplicated or
transferred between genomes more easily. This work sheds light on the apparent ease
with which two-component systems have expanded to become the dominant signaling
system in bacterial genomes and, more generally, how a small number of gene families
can be responsible for signal transduction in all organisms.
Thesis Supervisor: Michael T. Laub
Title: Associate Professor of Biology
Capra1 2
ACKNOWLEDGEMENTS
This work would not have been possible without the help and support of a large number
of people. I'd like to thank the following people in particular:
I'd first like to thank my advisor Mike Laub for all of his scientific guidance. It's been a
great run and a great graduate experience. You've really made the lab a fantastic place to
do science.
My thesis committee, Amy Keating and Aviv Regev for all of their insightful comments
on the project, and their willingness and timeliness in writing me so many letters of
recommendation.
Mike Springer for agreeing to be the outside member on my committee.
The lab as a whole-the amount of knowledge and scientific interest in the lab is
impressive. I'd like to thank everyone for their willingness to help and for making my
graduate experience what it was. Within the lab there are certain people who I'd like to
single out. I need to especially thank Barrett. The immense number of profiles wouldn't
have been the same without the company in the hot room. Your knowledge and instincts
were invaluable in helping me to decide what path to take. All of my papers would have
taken a lot longer if not for the numerous protein purifications that you were willing to
help with. You have been my sounding board scientifically a great friend. I couldn't
imagine the Laub lab without you. I'd also like to thank Erin, Kasia, and Christos for
welcoming me into the lab and for paving the way. Christos and Diane for being
awesome baymates and ensuring that I spent very little time in lab alone. Anna for being
a great addition to the specificity side of the lab and always being willing to bounce ideas
around with me and to distract me with coffee. And finally, the pilates group for
convincing me to leave lab at a reasonable hour once a week for cannolis and exercise.
My classmates for going on this journey with me and for all of the random Boston
adventures. I'm so thankful to have met you. I'd especially like to thank Lori for the
coffee chats and for being my fifth floor buddy. Also the trivia group-Jen, MK, Josh,
Jason, Jenny, and Lori for trying make sure that we see each other outside of lab.
My roommates, Ashley, Sarah, and Julia, and my honorary roommate Max. I can't
believe it's been five years. I don't know what I would have done without you guys.
From family dinners to scientific conversations to random adventures around Boston, I'll
miss you guys and I'm so happy that we decided to embark on this journey together.
Finally my family, for their love and support in all that I do.
Capra 13
TABLE OF CONTENTS
Chapter 1: Introduction.........................................................................
13
O verview ......................................................................................................................
14
The two-component signal transduction paradigm...............................................
15
Evolution of genome content and gene number....................................................
18
Mechanisms for evolving changes in two-component signaling gene content......... 23
Gene fusions, rearrangements, and duplications....................................................
26
Evolution of signaling protein structure and function ........................................
28
Histidine kinase sensory domain evolution ..........................................................
28
Divergence and evolution of pathway outputs......................................................
32
Dim erization specificity........................................................................................
37
Evolution of phosphotransfer specificity and the insulation of pathways .............
38
Research approach ................................................
45
Acknowledgements .................................................................................................
48
References....
49
................................................
Chapter 2: Systematic dissection and trajectory-scanning mutagenesis
of the molecular interface that insures specificity of two-component
signaling pathways..................................................................................
57
A bstract........................................................................................................................
58
Author Summary ....................................................................................................
59
Capra 14
Introduction .................................................................................................................
60
Results ..........................................................................................................................
63
Identification of coevolving residues in cognate kinase-regulator pairs ..............
63
Rew iring response regulator specificity................................................................
67
Alanine-scanning mutagenesis and the role of individual residues ......................
70
Characterization of all intermediates along the mutational trajectories separating
76
EnvZ and RstB ......................................................................................................
A complete specificity map of the mutational trajectories separating EnvZ/OmpR
79
and RstB/RstA ......................................................................................................
85
Discussion ....................................................................................................................
Determ inants of specificity in paralogous protein fam ilies ...................................
85
Evolutionary implications......................................................................................
87
Rational rewiring of two-com ponent signaling pathways ....................................
90
Final perspective ....................................................................................................
91
M aterials and M ethods...........................................................................................
93
Sequence analysis .................................................................................................
93
Clustering ..................................................................................................................
93
Protein purification ...............................................................................................
94
Autophosphorylation and phosphotransfer reactions.............................................
95
Acknowledgem ents .................................................................................................
97
References....................................................................................................................
98
Capra 5
Chapter 3: Adaptive mutations that prevent crosstalk enable the
expansion of paralagous signaling protein families...............................100
Abstract.................................................
....
101
Introduction...............................................................................................................
102
R esults........................................................................................................................
106
To identify vertical inheritance of PhoR and PhoB................................................
106
Identification of adaptive mutations that prevent cross-talk in vitro ......................
109
Avoidance of cross-talk is a significant selective pressure.....................................
115
Different adaptive mutations prevent cross-talk in other proteobacterial clades.... 121
Global optimization of signaling fidelity ................................................................
124
Discussion ..................................................................................................................
126
Materials and Methods.............................................................................................
130
Identification of orthologs and construction of gene trees......................................
130
Growth conditions and strain construction ..........................................................
131
Protein purification and phosphotransfer assays............;........................................
136
Growth and competitive fitness assays...................................................................
136
M icroarray analysis.................................................................................................
137
Acknowledgements .................................................................................................
138
References..................................................................................................................
139
Chapter 4: Spatial tethering of kinases to their substrates relaxes
evolutionary constraints on specificity ...................................................
142
Capra 16
Abstract......................................................................................................................143
Introduction...............................................................................................................
144
Results........................................................................................................................
149
Hybrid kinases show reduced amino acid coevolution between kinase and receiver
dom ains ...................................................................................................................
149
Hybrid kinases exhibit lim ited phosphotransfer specificity....................................
151
Physical attachment of a receiver domain reduces signaling cross-talk .................
155
Hybrid kinases lacking their receiver domains likely cross-talk to other response
regulators in vivo ....................................................................................................
161
Hybrid histidine kinases are under reduced selective pressure to diversify ........... 163
Discussion ..................................................................................................................
167
M aterials and M ethods.............................................................................................
172
Sequence analyses...................................................................................................
172
Strain construction and growth conditions .............................................................
172
Protein purification and phosphotransfer assays.....................................................
174
Acknowledgerm ents ...................................................................................................
175
References..................................................................................................................
176
Chapter 5: Conclusions and future directions .......................................
178
Conclusions................................................................................................................
179
Future Directions ..................................................................................................
181
Capra 7
H PT specificity and expansion ...............................................................................
181
Explorations of sequence space ..............................................................................
184
Sequence space in the response regulator/DN A interaction ...................................
190
Concluding rem arks .................................................................................................
194
R eferences: ................................................................................................................
196
Capra 18
TABLE OF FIGURES AND TABLES
Chapter 1: Introduction
Figure 1.1 Overview of two-component signal transduction...............................
17
Figure 1.2 Diversity of two-component signaling gene content in bacterial genomes
...................................................................................................................................
19
Figure 1.3 Evolution of sensory dom ains. ...........................................................
31
Figure 1.4 Evolution of transcriptional circuits controlled by two-component
33
p athw ay s. ..................................................................................................................
Figure 1.5 Amino acid coevolution in two-component signaling proteins.......... 39
Figure 1.6 Insulation of two-component pathways following gene duplication...... 42
Chapter 2: Systematic dissection and trajectory-scanning mutagenesis
of the molecular interface that insures specificity of two-component
signaling pathways
Figure 2.1 Adjusted mutual information analysis of amino acid covariation in two64
com ponent proteins...............................................................................................
Figure 2.2 Identification of coevolving amino acids in cognate pairs of histidine
65
kinases and response regulators.............................................................................
Figure 2.3 Identification of coevolving amino acids in cognate pairs of histidine
kinases and response regulators.............................................................................
66
Figure 2.4 Rewiring the specificity of response regulators. ................................
68
Figure 2.5 Alanine-scanning mutagenesis of EnvZ.............................................
72
Capra 19
Figure 2.6 Alanine scanning mutagenesis of EnvZ. ...........................................
74
Figure 2.7 Dephosphorylation of OmpR~P by EnvZ alanine mutants................. 75
Figure 2.8 Converting the phosphotransfer specificity of EnvZ to match RstB and
vice versa. .................................................................................................................
77
Figure 2.9 Complete trajectory-scanning mutagenesis of EnvZ and OmpR. ...... 81
Figure 2.10 Hierarchical clustering of trajectory-scanning mutagenesis of EnvZ and
O m p R ........................................................................................................................
82
Figure 2.11 Mutational trajectories from EnvZ/OmpR to RstB/RstA .................
88
T able 2.1 Prim ers ................................................................................................
94
Chapter 3: Adaptive mutations that prevent crosstalk enable the
expansion of paralogous signaling protein families
Figure 3.1 Phosphotransfer specificity of PhoR is different in c-
and y-
proteob acteria..........................................................................................................
10 7
Figure 3.2 Phylogenetic analyses of PhoR and PhoB............................................
108
Figure 3.3
Substituting y-like
specificity
residues into
c-PhoR increases
phosphorylation of N trX . ........................................................................................
111
Figure 3.4 The divergent evolution of NtrX after duplication led initially to crosstalk w ith PhoR in c-proteobacteria.........................................................................
112
Figure 3.5 Time courses of phosphotransfer from C. crescentus PhoR specificity
m utan ts....................................................................................................................
1 13
Figure 3.6 Cross-talk between PhoR(TV) and NtrX leads to a growth defect and
fitness disadvantage in phosphate-limited media. ..................................................
116
Capra I 10
Figure 3.7 The specificity substitutions AS-+TV in C. crescentus PhoR lead to a
selective disadvantage in phosphate-limited media................................................
117
Figure 3.8 Extant two-component signaling pathways are insulated from each other
122
at the level of phosphotransfer................................................................................
Figure 3.9 Orthogonality of specificity residues in E. coli and C. crescentus twocom ponent signaling proteins.................................................................................123
Figure 3.10 Adaptive divergence of duplicated signaling pathways involves the
elim ination of cross-talk. ........................................................................................
127
T able 3.1 Strains and plasm ids...........................................................................
131
T ab le 3 .2 P rim ers ..................................................................................................
134
Chapter 4: Spatial tethering of kinases to their substrates relaxes
evolutionary constraints on specificity
Figure 4.1 Amino acid coevolution analysis of hybrid histidine kinases. ............ 145
Figure 4.2 Amino acid coevolution analysis of hybrid histidine kinases. ............. 150
Figure 4.3 Hybrid histidine kinases show reduced phosphotransfer specificity in
v itro.........................................................................................................................
15 3
Figure 4.4 Phosphotransfer profiles against receiver domains. .............................
155
Figure 4.5 Phosphotransfer profiles against response regulators...........................
156
Figure 4.6 Hybrid kinases lacking their receiver domains exhibit cross-talk........ 157
Figure 4.7 Hybrid kinases lacking their receiver domains exhibit cross-talk........ 160
Figure 4.8 Genome-wide sets of specificity residues from two-component signaling
p ro te in s....................................................................................................................
16 5
Capra I 11
Figure 4.9 Specificity residues are conserved among hybrid histidine kinases..... 166
Figure 4.10 Model for changes in specificity residues following duplication of
canonical and hybrid histidine kinases. ..................................................................
168
T ab le 4.1 P rim ers ...................................................................................................
173
Chapter 5: Conclusions and future directions
Figure 5.1 Evolution and specificity of HPT domains...........................................
182
Figure 5.2 Library screen to determine sequence space. ....................................
186
Figure 5.3 Two models for insulation of pathways post-duplication. ...................
188
Figure 5.4 Distribution of E. coli response regulators in a set of well-studied yproteob acteria..........................................................................................................
192
Figure 5.5 Evolution of transcriptional networks post-duplication. ......................
193
Capra 112
Chapter 1
Introduction:
Evolution of two-component signal transduction systems
This chapter is adapted from work originally published as Emily J. Capra and Michael T. Laub.
2012. Annu Rev Microbiol. 66:325-47.
EJC and MTL wrote the manuscript and designed the figures. EJC made all of the changes from
the original manuscript.
Capra 113
Overview
Two-component signal transduction systems are a predominant means by which bacteria
sense and respond to their environments. These systems are generally comprised of a
receptor histidine kinase that senses a specific signal and translates that input into a
desired output through the phosphorylation of its cognate response regulator. The success
of two-component signaling systems as a strategy for coupling changes in the
environment to changes in cellular physiology is underscored by their prevalence
throughout the bacterial kingdom. These signaling proteins have been found in the
genomes of nearly all sequenced bacteria, with the majority of species encoding dozens,
and sometimes hundreds, of two-component proteins. They have been uncovered in
countless genetic screens and shown to respond to an enormous range of signals and
stressors (for reviews, see (Laub, 2011; Stock et al., 2000).
Although tremendous progress has been made in understanding the structure and function
of some individual systems, additional aspects of these pathways have recently garnered
significant interest. How does a single cell coordinate so many highly related signaling
pathways? The kinases and regulators encoded by a given organism are often highly
similar at the sequence and structural levels, yet cells are able to match specific inputs to
the desired output. How is unwanted cross-talk avoided? Do cells leverage the similarity
of these proteins to integrate signals or diversify responses?
Histidine kinases and response regulators have an intrinsic modularity that separates
signal input, phosphotransfer, and output response; this modularity has allowed bacteria
to dramatically expand and diversify their signaling capabilities. Gene duplication and
lateral (horizontal) gene transfer (LGT) provide the raw materials for producing new
Capra| 14
pathways and, in either case, the introduction of new signaling proteins requires a flurry
of changes if the new proteins are to be maintained over the course of evolution. The new
pathway must gain a new function to provide a selective advantage and to warrant
maintenance in the genome. Domain shuffling likely plays a critical role and recent work
has begun to reveal how, at a mechanistic level, this process occurs. New pathways must
also avoid cross-talk with other pathways, and vice versa, leading to changes in the
specificity determinants of these pathways at multiple levels, including receptor
dimerization and kinase-substrate partnering. Recent work has begun to reveal the
molecular basis by which two-component proteins evolve. How and why do orthologous
signaling proteins diverge? How do cells gain new pathways and recognize new signals?
What changes are needed to insulate a new pathway from existing pathways? What
constraints are there on gene duplication and lateral gene transfer?
The two-component signal transduction paradigm
The eponymous two-component signaling pathway contains a sensor histidine kinase and
a cognate response regulator (Figure 1.lA). Upon receipt of a stimulus, the histidine
kinase catalyzes an autophosphorylation reaction on a conserved histidine residue. This
phosphoryl group is then transferred to a conserved aspartate on a cognate response
regulator. Phosphorylation of the regulator usually drives a conformational change that
activates its output response, often leading to changes in gene expression (Gao et al.,
2007; Gao and Stock, 2009; Gao and Stock, 2010; Stock et al., 2000). These systems thus
represent versatile, powerful ways to couple changes in external or environmental
conditions to corresponding changes in cellular physiology and gene expression. In most
cases,
histidine
kinases
are bifunctional
such
that,
when
not
stimulated
to
Capra 15
autophosphorylate, they act as phosphatases for their cognate response regulators; thus it
is ultimately the ratio of kinase to phosphatase activity that is responsible for modulating
the output response (Huynh and Stewart, 2011; Jin and Inouye, 1993; Yang and Inouye,
1993). In some cases, input signals may promote the phosphatase state rather than
stimulating autophosphorylation (Raivio and Silhavy, 1997).
All histidine kinases contain two highly conserved domains, the dimerization and
histidine phosphotransfer (DHp) domain, which harbors the conserved histidine that is
the site of both the autophosphorylation and phosphotransfer reactions, and the catalytic
and ATP-binding (CA) domain. Histidine kinases also usually contain at least one (and
often several) additional domain N-terminal to the DHp domain (Figure 1.11B). For the
vast majority of kinases this includes 1-13 transmembrane domains (Galperin, 2005) with
signal recognition occurring primarily in the periplasmic or extracellular portion of the
protein. Although some common domains have been noted, signal recognition domains
tend to be more variable than the other domains. Most kinases also have at least one
domain between the transmembrane and DHp domains, with PAS, HAMP, and GAF
domains by far the most common (Galperin et al., 2001). These domains can either relay
signals from the periplasmic sensory domains to the DHp and CA domains or, in some
cases, directly recognize cytoplasmic signals (Moglich et al., 2009b; Parkinson, 2010).
Response regulators share a common, well-conserved receiver domain (RD) that
catalyzes phosphotransfer from its cognate histidine kinase. Phosphorylation then
promotes a conformational change on one face of the receiver domain, which in turn
effects an output (Gao et al., 2007). In single-domain response regulators, the
Capra 116
Signal -N
A
B
Hybrid histidine
Histidine kinases:
kinase
mPA
Signal
CAKi
ATP
Histidine
kinase
CA
ATP
-
.-...
H
-..
-'v. D
RD
Response regulators:
ATP
CA
-D1
Membi ane
H
D
Response
regulator
Histidine
phosphotransferase
RD
thyltransferase)
Figure 1.1 Overview of two-component signal transduction.
(A) In the canonical two component pathway (left), the CA domain of a histidine kianse binds ATP
and autophosphorylates a conserved histidine in the DHp domain. The phosphoryl group is then
transferred to an aspartate in the RD of the cognate response regulator, activating its output
domain to effect cellular changes, often through changes in transcription. In a phosphorelay
system (right), a hybrid histidine kinase autophosphorylates and transfers its phosphoryl group
intramolecularly to a RD. A histidine phosphotransferase (HPT) then shuttles the phosphoryl
group to a soluble response regulator that effects a pathway output. (B) Common domain
organizations of histidine kinases and response regulators are shown. For histidine kinases, the
DHp and CAdomains are shown with comnon intracellular domains: Per-Arnt-Sim (PAS), histidine
kinase and methyl-accepting proteins (HAMP), and cGMP-specific phosphodiesterase adenyl
cyclase and FhIA (GAF). Note that some kinases have multiple copies of such domains. Two TM
domains are shown on the kinases, but kinases can harbor from 0-13 TM domains. A wide range
of sensory domains (not shown) are often found in the periplasmic portions of membrane-bound
histidine kinases. For response regulators, the conserved receiver domain is shown alone or with
common output domains including a DNA-binding domain (DBD), a AAA+ and DNA-binding
domain, a GGDEF domain involved in cyclic-di-GMP synthesis, or a CheB-like methyltransferase
domain.
conformational change in the receiver domain allows the protein to directly produce an
output response. Most response regulators, however, contain a DNA binding output
domain (Galperin, 2006) (Figure 1.1 B). For these regulators, phosphorylation induces
homodimerization of the receiver domain, stimulating DNA binding and leading to
Capra 117
transcriptional changes. Other common output domains include diguanylate cyclases and
methyltransferases.
A common variant of the two-component paradigm is the so-called phosphorelay
(Burbulys et al., 1991) (Figure 1.1 A). These extended pathways typically initiate with a
hybrid kinase, which is a histidine kinase with a receiver domain fused to its C-terminus.
After autophosphorylation and an intramolecular phosphotransfer to the receiver domain,
the phosphoryl group is shuttled to a histidine phosphotransferase (HPT), and from there
to a terminal response regulator that effects an output. Nearly 25% of all histidine kinases
are hybrids (Cock and Whitworth, 2007), suggesting that phosphorelays are common.
Evolution of genome content and gene number
Two-component signaling proteins are among the most prevalent bacterial genes, and
histidine kinases and response regulators constitute two of the largest paralogous gene
families in bacteria (Galperin, 2005). Both kinases and regulators are easily identified by
sequence homology, in contrast to many eukaryotic signaling systems in which protein
kinases are easily identified but their substrates are not. Many histidine kinases are
encoded in the same operon as their cognate regulators, allowing for cognate pairs to be
identified through sequence analysis. Census-taking is thus straightforward and easily
applied to fully sequenced bacterial genomes (Figure 1.2A). Such analyses have revealed
that the total number of two-component genes per genome typically grows as a square of
the genome size (Galperin, 2005) (Figure 1.2B). In addition, the number of twocomponent genes appears to correlate strongly with ecological and environmental niche
(Alm et al., 2006; Galperin, 2005; Galperin et al., 2001; Koretke et al., 2000). Bacteria
Capra 118
A
140
1
I
1
120 -
I
Myxococcus xanthus
-
0
100
Geobacter bemidjiensis
Ralstonia metallidurans
*
80 -*
0
0.
U)
2
E
V
*
60
4O -
40 -
c
Nostoc punctiforme
omnas aeruginosa
I?P
-
crescentus
sCaulobacter
Bacillus Suts
Rhoaococcus jostii
*
Eschenc .i
**
**
Bacteroides thetaiotaomicron
20 Re e sia ticettsfi
k
Onientia tsutsugamushi
0
0
20
40
60
120
100
80
140
160
180
Number of histidine kinases
B
I
300
U)U
C
I
I
I
250
Myxococcus xanthus
bemidjiensis
200
-Geobacter
5
100say
rknstarg
05
E4
se sils
Scec
*
50
otaoricron
s sfhe
notabeS
talidurans
t
o pRai
T
Z
I
Nostoc punctiforme
0.
C
I
jost
w dRhodococcus
iao00li
0
0
pathays
ypiallycompiseoer
1,000
2,000
3,000
4,000
5,000
6,000
7,000
inascend
ont
genome
in'neultr
Total number of proteins
8,000
9,000
hnterai
10,000
snt11
Figure 1.2 Diversity of two-component signaling gene content in bacterial
genomes.
(A) Plot showing the number of histidine kinases and response regulators in set of bacterial
genomes. Generally, most genomes contain equal numbers of kinases and regulators, as
pathways typically comprise one kinase and one cognate regulator. When the ratio is not 1:1,
there are usually more kinases than regulators, suggesting response regulators may sometimes
integrate signals from multiple kinases. (B) Plot showing the number of two-component proteins
as a function of genome size for the same organisms as in panel A. Each plot is based on 504
bacterial genomes with data taken from (Galperin et al., 2010). A handful of well-studied and
notable species are marked with red squares.
Capra 119
that live primarily in constant environments typically encode relatively few twocomponent signaling genes, even taking into account their smaller genome sizes and
characteristic reductive genome evolution. In the extreme, many obligate intracellular
parasites and endosymbionts harbor only a few pathways or sometimes none at all, as
with Mycoplasma and Amoebophilus. By contrast, bacteria that inhabit rapidly changing
or diverse environments typically encode large numbers of these signaling proteins.
Extreme cases include Myxococcus xanthus with 136 histidine kinases and 127 response
regulators and Nostoc punctiforme with 160 kinases and 98 regulators (Ulrich and Zhulin,
2010) (Figure 1.2). In some species, nearly 3% of the genome encodes for histidine
kinases alone (Galperin, 2005). These patterns of gene content strongly suggest that
organisms expand their set of two-component signaling genes to help adapt to
fluctuations in their environment.
Although most abundant in the genomes of gram-negative bacteria and cyanobacteria,
two-component signaling genes are found in all three domains of life (Koretke et al.,
2000; Schaller et al., 2011). However, they are considerably less abundant in archaea and
eukaryotes. The majority of systems found in eukaryotes involve hybrid kinases and
phosphorelays; whether there is selective pressure against canonical systems is unknown.
Many of the archaeal and eukaryotic systems likely originated through multiple,
independent lateral gene transfers from bacteria (Kim and Forst, 2001; Koretke et al.,
2000); plants likely gained two-component pathways through the integration of
chloroplast genes into the nuclear genome (Martin et al., 2002). In plants, the twocomponent genes obtained through lateral transfer likely expanded through duplication
Capra 120
and diversification and now play integral roles in diverse developmental pathways (Ren
et al., 2009).
Whereas two-component genes are found in yeasts, filamentous fungi, slime molds, and
plants, they are conspicuously absent from higher eukaryotes and metazoans. The
absence of two-component signaling proteins from humans, combined with their welldocumented role in bacterial pathogenesis (Gooderham and Hancock, 2009; Miller et al.,
1989), has made these proteins attractive new targets for antibiotic development (Gotoh
et al., 2010). Indeed, a recent study sequenced individual isolates over the course of a
Burkoholderiadolosa outbreak of patients with cystic fibrosis and discovered that a twocomponent system, FixL/FixJ was under the strongest positive selection of any gene over
the course of infection (Liebennan et al., 2011). Evolutionarily, the absence of twocomponent systems in metazoans begs the question of why they were supplanted as the
primary means of signaling by pathways employing serine, threonine, and tyrosine
phosphorylation. Although a definitive answer is lacking, the intrinsic lability of
phosphoryl groups on aspartates may have contributed. In eukaryotes, a need for longer,
more stable outputs may have been desirable, and perhaps necessary, for transmitting
signals from the cell membrane to the nucleus without signal loss en route in the fonn of
phosphoryl group hydrolysis. Consistent with this idea, many of the two-component
pathways in eukaryotes do not regulate transcription and instead target other cytoplasmic
proteins. For example, in Saccharomyces cerevisiae, the Slnl-Ypd1-Sskl phosphorelay
modulates the activity of a MAP kinase pathway that is also located in the cell membrane
(Posas et al., 1996). Nevertheless, there are cases of eukaryotic response regulators that
directly affect transcription, particularly
in plants.
In these cases a histidine
Capra 21
phosphotransferase typically shuttles phosphoryl groups from a cytoplasmic hybrid
histidine kinase to a response regulator in the nucleus that is constitutively associated
with the DNA (Grefen and Harter, 2004; Imamura et al., 2001). Signal transmission may
be successful in these cases because a histidyl-phosphate moiety is considerably more
stable than an aspartyl-phosphate moiety.
Where did two-component signaling pathways, in any organism, evolve from in the first
place? Given their ancient origin, an unequivocal answer to this question may not be
attainable. However, one clue is that histidine kinases share distant homology in their
ATP-binding domains with Hsp90, the mismatch repair protein MutL, and type II
topoisomerases (Dutta and Inouye, 2000; Dutta et al., 1999). These proteins, members of
the so-called GHKL superfamily, are thought to bind ATP in similar ways and share
significant structural similarities; in some cases this domain is used to drive ATP
hydrolysis, and in the case of histidine kinases the y-phosphoryl group is transferred to a
histidine in the DHp domain. It is thus plausible that histidine kinases emerged from one
of these ATPases. In contrast to histidine kinases, there are no such weak homologies for
response regulators and their origin remains a mystery.
There are likely two sources of histidine phosphotransferases. Some, particularly those
that are monomeric (Ulrich et al., 2005; Xu et al., 2009), may have evolved de novo from
a range of other proteins, as there are few structural and sequence requirements to
function as a histidine phosphotransferase beyond a phosphorylatable histidine within an
ax-helical bundle. Others are dimeric and may have evolved through the degeneration of
histidine kinases. For example, Bacillus subtilis SpoOB has two domains with significant
similarity to those in histidine kinases (Varughese et al., 1998; Zapf et al., 2000). The
Capra 22
domain that contains the crucial histidine is structurally similar to the DHp domain of
histidine kinases and the other is topologically and structurally similar to a CA domain
but lacks key residues usually involved in ATP binding. A similar scenario of recruitment
and degeneration of a histidine kinase may hold for the phosphotransferase ChpT in
Caulobactercrescentus (Biondi et al., 2006). In general, however, evolutionary analysis
of histidine phosphotransferases has been limited by the difficulty of identifying these
proteins from sequence alone, in contrast to histidine kinases and response regulators.
Mechanisms for evolving changes in two-component signaling gene
content
Given the prevalence of two-component signaling pathways in bacterial genomes, it is
natural to ask how new proteins and pathways arise. The possibilities fall into two broad
categories: gene duplication and divergence, sometimes also referred to as lineagespecific expansion (LSE), and lateral gene transfer (LGT). To assess the contributions
made by these two mechanisms, one study systematically examined the origins of
histidine kinases from 207 genomes, using BLAST to identify the closest homologs of
each kinase (Alm et al., 2006). For those most closely related to a kinase within the same
genome, gene duplication, or lineage-specific expansion, was inferred as the source. If
the closest homolog was from a closely related species, and if a gene tree built from all
homologs matched a species tree, the kinase was classified as ancient and vertically
transmitted. If, however, the closest homolog for a given kinase was from a distantly
related species, lateral gene transfer was invoked. This interpretation assumes that
multiple gene losses are less parsimonious and hence less likely to have occurred.
However, gene loss occurs at very high rates in bacteria. In addition, inferences of lateral
Capra 123
transfer can be confounded by the inaccuracy of sequence-based distances and
heterotachy, the notion that substitution rates in different lineages often vary significantly
(Kurland et al., 2003).
Nevertheless, lateral gene transfer of two-component pathways undoubtedly has occurred
and these systematic studies provide a general sense of the frequency, both across all
species and within individual genomes (Alm et al., 2006). Overall, lineage-specific
expansion, or gene duplication, appears to explain the origin of the vast majority of
kinases. However, the relative balance of duplication and lateral transfer varies
substantially from species to species. For example, in Streptomyces coelicolor, essentially
all of its 140 histidine kinases appear to be ancient or derived from lineage-specific
expansions. By contrast, in Pseudomonas syringae and Ralstonia solanacearum,many of
the recently derived kinases probably came from lateral transfer events.
The lateral transfer of genes in bacteria can occur in several ways, including through
phage and plasmids, by direct conjugation, or by competence and the direct uptake of
extracellular DNA. There are examples of two-component signaling genes encoded on
plasmids, such as the VanR-VanS system found in enterococci that senses and responds
to vancomycin (Arthur et al., 1992; Wright et al., 1993). In R. solanacearum,many of the
laterally derived histidine kinases are encoded on a megaplasmid that may have moved
laterally (Salanoubat et al., 2002). There are also cases of two-component signaling
proteins encoded on pathogenicity islands, such as the SpiR-SsrB system in Salmonella,
which frequently move through conjugation (Deiwick et al., 1999). However, for many
chromosomally encoded two-component genes derived by lateral transfer, the mechanism
of transfer remains difficult to infer.
Capra 124
Both gene duplication and lateral transfer events have occurred more frequently than
suggested by phylogenetic analyses. However, in most cases the newly introduced genes
were likely eliminated from the genome, and thus are no longer present in extant species.
Bacteria typically have high rates of gene loss through mutation and deletion. Indeed,
histidine kinases and response regulators are among the most common pseudogenes
present in bacterial genomes (Liu et al., 2004); these pseudogenes likely arose through
relatively recent duplications or lateral transfers, and were then inactivated, but have not
yet been removed from the genome. To be fixed in a population, duplicated or laterally
transferred genes must provide a substantial selective advantage within a relatively short
period, as gene loss and pseudogeneization occur rapidly in bacteria (Hooper and Berg,
2003; Kuo and Ochman, 2010).
The function of a particular two-component system can also influence its evolutionary
history. For example, an analysis of six species of Xanthomonas compared the
complement of signaling genes present in each genome and found extensive gene loss
(Qian et al., 2008). Notably, those pathways involved in Xanthomonas pathogenesis were
never lost or duplicated, whereas other, presumably less critical, pathways experienced
more flux. Similarly, in C. crescentus, where two-component signaling proteins play
important roles in cell cycle progression and development pathways, those that are
essential for viability are highly-conserved in other Alphaproteobacteria,whereas those
that are non-essential in C. crescentus are less well-conserved (Skerker et al., 2005). In
most species there is probably a core set of two-component proteins that is maintained
and relatively fixed, and an additional set that can be lost, or modified, more easily.
Capra 125
This notion of fixed core signaling genes and malleable auxiliary factors has been wellcharacterized in the context of bacterial chemotaxis, which centers on a two-component
pathway, CheA-CheY. In Escherichia coli, where chemotaxis has been best studied,
signal recognition requires a methyl-accepting chemoreceptor protein (MCP) and an
adaptor protein CheW. Virtually all chernotactic bacteria encode orthologs of these core
components: MCP, CheW, CheA, and CheY (Wuichet and Zhulin, 2010). In contrast,
many of the auxiliary components, including the methyltransferase CheR and the
methylesterase CheB that influence signal adaptation, are not universally conserved and
are often missing or replaced by other types of regulators (Wuichet and Zhulin, 2010).
Gene fusions, rearrangements, and duplications
Many two-component genes are encoded in operons as cognate kinase-regulator pairs,
allowing for the duplication or lateral transfer of an intact signaling pathway. It is rare to
see operon shuffling and the mixing and matching of genes encoded in operons. Hence,
for a given kinase-regulator pair, the orthologs are also usually found together in an
operon and in the same relative order (Koretke et al., 2000; Whitworth and Cock, 2009).
Fusions of kinases and regulators to create hybrid kinases also seem to be rare, but there
are some examples. For instance, analysis of six species of Xanthomonas found that the
individual domains of a hybrid histidine kinase in one species were most similar to, and
likely derived from, an operonic kinase-regulator pair encoded as separate open reading
frames in a closely related species (Qian et al., 2008). Such fusions probably occur
through the mutation of stop codons in operons where the histidine kinase is upstream of
the response regulator, although hybrid kinases may also form through the fusion of
previously separated genes (Qian et al., 2008; Whitworth and Cock, 2009; Zhang and
Capra 126
Shi, 2005). As might be expected, fusion events that create hybrid kinases are rare for
response regulators that contain DNA-binding output domains (Cock and Whitworth,
2007; Zhang and Shi, 2005). There are, however, examples of such hybrid kinases
(Sonnenburg et al., 2006), but the mechanism by which these systems regulate
transcription remains unclear.
Although E. coli encodes 55 of its 62 two-component genes in operons, many organisms
encode a substantial fraction of their two-component genes as orphans. Frequently only
one gene from an operon is duplicated (or both are duplicated and one is lost) resulting in
the production of orphan two-component signaling genes. An orphan kinase, however,
may retain the ability to phosphorylate the regulator in the operon from which it was
derived. Such duplication events, coupled with a change in kinase input domain, may be
a primary mechanism for generating cross-regulated systems in which multiple,
independent signals can trigger the same response. A classic example is in B. subtilis, in
which each of the five orphan kinases KinA/B/C/D/E, which probably evolved through
duplication, can each phosphorylate SpoOF and initiate the sporulation phosphorelay
(Stephenson and Hoch, 2002). Similarly, duplication of only the response regulator from
a given kinase-regulator pair can lead to a scenario in which a single sensor kinase can
drive multiple outputs. For example, in cyanobacteria NblS-RpaB forms an essential twocomponent system. During divergence of the cyanobacteria in the clade including
Synechococcus species, a duplication of RpaB produced a second response regulator
SrrA. This regulator retained the ability to be phosphorylated by NblS, but appears to
affect transcription manner different than that by RpaB (Lopez-Redondo et al., 2010).
Capra 127
Evolution of signaling protein structure andfunction
Gene duplication and lateral gene transfer ultimately provide the raw material for
generating new two-component signaling pathways. But what happens immediately after
new signaling genes are introduced? Owing to large population sizes and selective
pressure to minimize genome size (Mira et al., 2001), new signaling proteins presumably
must quickly gain new functions to be retained. There are undoubtedly many mutations
that must occur to produce a pathway that can respond to a new input or effect a new
output. These mutations presumably include single amino acid substitutions, although
rapid changes in function may rely heavily on larger-scale rearrangements such as
domain shuffling. Below I summarize the current understanding of how cells generate
new signaling functions from duplicated genes, focusing on (i) changes in kinase sensory
domains and pathway inputs, (ii) changes in response regulators and pathway outputs,
and (iii) changes required to insulate new pathways from existing pathways, before
describing the work that I have done, particularly regarding the question of interaction
specificity between kinase and regulator.
Histidine kinase sensory domain evolution
After the duplication of a histidine kinase, whether alone or with a cognate response
regulator, the duplicate histidine kinases must differentiate themselves and find new roles
within the signaling network of a cell. One mechanism to accomplish this is through
changes in the sensory domains of one or both kinases (Cheung and Hendrickson, 2010;
Krell et al., 2010). For most orthologous kinases, the sensory domains are less wellconserved than their catalytic domains. The ability to sense a new signal often arises via
domain shuffling, which may occur coincident with, or shortly after, a duplication. Over
Capra 28
70% of recently duplicated histidine kinases show an input domain structure different
from that of their closest paralog (Alm et al., 2006) (Figure 1.3A). Domain shuffling can
also occur between histidine kinases and other proteins. Sequence analyses indicate that
the sensory domains of some histidine kinases are closely related to domains found on
other types of proteins, including serine/threonine kinases (Zhulin et al., 2003),
chemotaxis proteins, and diguanylate cyclases (Zhang and Hendrickson, 2010).
The domain shuffling observed in histidine kinases suggests that these proteins are
intrinsically modular and, consequently, that the rational design of new kinases may be
possible. Indeed, several groups have successfully fused the conserved phosphotransfer
and catalytic domains from a histidine kinase to the sensory domain of another kinase, or
even the sensory domain of completely unrelated proteins. The first such example,
dubbed Taz, is a chimeric protein that fused the sensory domain of the aspartate
chemoreceptor Tar with the DHp and CA domains of the model histidine kinase EnvZ,
producing an aspartate-responsive kinase (Utsumi et al.,
1989). In addition to
demonstrating the fundamental modularity of histidine kinases, Taz has been used to
dissect the functions and activities of EnvZ in vivo (Dutta et al., 2000; Jin and Inouye,
1993; Zhu and Inouye, 2003). Other functional chemoreceptor-EnvZ constructs have also
been made (Baumgartner et al., 1994; Rampersaud et al., 1991).
How does domain shuffling, either during evolution or during rational construction of
chimeric proteins, produce successful, signal-responsive proteins? Is there a particular
way in which sensory domains must be fused to the catalytic domains to function? These
questions were recently examined in the context of a chimeric protein that fused a lightsensing PAS domain, taken from the B. subtilis protein YtvA (which is not a kinase),
Capra 129
with the DHp and CA domains of the histidine kinase FixL from Bradyrhizobium
japonicum. Successful fusions of the PAS domain to FixL led to light-responsive changes
in FixL signaling and FixL-FixJ-dependent gene expression (Moglich et al., 2009a).
Successful fusions had linkers, which form coiled coils, separating the PAS and DHp
domains that differed in length by exactly seven amino acids. Inspection of other
histidine kinases containing PAS domains further revealed that the linkers are of variable
lengths, but often differ by multiples of seven. Together, these results suggest that
maintaining the heptad periodicity of the coiled-coil linker may be critical to the
construction of functional chimeras, either during evolution or for rational engineering
purposes. Further work demonstrated that, by following similar rules, multiple PAS
domains could be engineered into the same kinase, allowing it to integrate multiple
signals (Moglich et al., 2010). Naturally occurring histidine kinases also often have
multiple input domains, suggesting that partial gene duplications, in which only a single
input domain is duplicated, may be a common mechanism for generating input diversity.
In sum, these efforts to engineer novel proteins are not only producing valuable tools, but
are also providing important new insights into how domain shuffling occurs and how it
contributes to the origin of new two-component signaling pathways in nature.
An additional mechanism for acquiring new input signals is through accumulated
substitutions in a sensory domain rather than its complete replacement. A prime example
comes from the NarX and NarQ sensor kinases in E. coli (Figure 1.3B). A gene
duplication event led to the emergence of these two related kinases, although which is
more ancestral is unclear. Nevertheless, studies of signal recognition have demonstrated
that NarQ responds to both nitrate and nitrite whereas NarX responds preferentially to
Capra 130
A
B
DVU0680
DVU2546
DVU1968
DVU0081
DVUA0087
DVU0737
DVU0025
DVUO25
*c~~3f~
~NarXEC
DVU3061
DVU0092
P-Box sequences:
Sf
NarXKO S
NarQEC D
NarQHI
D
H
K
EI
IEl
Figure 1.3 Evolution of sensory domains.
(A) A tree of a recent lineage specific expansion in Desulfovibrio vulgaris shows the extent of
domain shuffling that can occur after duplication. These paralogs show differences in the number
and types of signaling domains, as well as in the presence and number of transmembrane
domains. The lineage specific expansion was identified from (Alm et al., 2006). A neighbor-joining
tree was constructed using the PHYLIP software package (Felsenstein, 1989) with another D.
vibrio kinase, DVU0680, as the outgroup. Only the DHp and CA domains of the kinases were
used to build the tree. Domains were identified using the Pfam database (Punta et al., 2012) and
colored according to the same scheme as used in Figure 1.1. Transmembrane domains were
predicted by TMHMM (Krogh et al., 2001). The lineage specific expansion was rapid, as shown
by the difficult to resolve branches between members of the expansion. The diversity in the
number of PAS domains could represent partial duplications of the histidine kinase. (B) The
crystal structure of the ligand binding domain of NarX shown in complex with N0 3 (Cheung and
Hendrickson, 2009). NarX autophosphorylates preferentially in the presence of N0 3 when
compared to NO2. NarQ, which is a paralog of NarX, autophosphorylates in response to both
NO 2 and N0 3 ~. A mutation of a lysine (shown in orange) to an isoleucine (shown in blue), causes
NarX to behave more like NarQ in that it responds equally to both NO 2 and N0 3 (Williams and
Stewart, 1997). The larger and more hydophobic isoleucine may cause a kink in the helices that
affect how they transduce the signal in response to ligand binding. Shown below is an alignment
of the P-boxes of NarX and NarQ orthologs from Escherichia coli (EC), Klebsiella oxytoca (KO),
and Haemophilus influenze (HI). All residues that are conserved throughout the alignment are
highlighted in gray, while the residue that determines NarX-like vs. NarQ-like ligand discrimination
is highlighted in blue.
nitrate (Rabin and Stewart, 1993). Although the periplasmic domains of NarQ and NarX
are significantly diverged, they do share substantial similarity, particularly in a region
critical to ligand binding (Cheung and Hendrickson, 2009). Notably, a single point
mutation in this region of NarX that substitutes a lysine with an isoleucine, as found at
the equivalent position in NarQ, reduced the ability of NarX to discriminate between
nitrate and nitrite, rendering a more NarQ-like response pattern (Williams and Stewart,
Capra 131
1997) (Figure 1.3B). This study highlights how the accumulation of single point
mutations is a plausible means of rapidly generating new and different inputs to twocomponent signaling pathways.
Divergence and evolution of pathway outputs
Within a two-component signaling pathway, the response regulator is the ultimate arbiter
of physiological change. How does the output of a response regulator evolve, and how
are new output responses generated by response regulators after they emerge through
duplication or following lateral transfer? As the majority of response regulators direct
changes in gene expression, the evolution of pathway outputs can be easily studied by
following changes in target genes.
One
of the
best-studied
examples
is the
PhoQ-PhoP
system
found
in the
Enterobacteriaceae.In response to low extracellular concentrations of Mg2 l, the histidine
kinase PhoQ drives phosphorylation of PhoP, which then regulates gene expression. The
direct regulon of PhoP has been mapped in both Salmonella enterica serovar
Typhimurium and Yersinia pestis (Perez et al., 2009), which probably shared a common
ancestor -200 million years ago. Strikingly, only three genes were directly regulated by
PhoP in both species: the autoregulated phoQ and phoP genes and slyB, which encodes a
lipoprotein thought to be a critical regulator of PhoQ activity (Figure 1.4A). There were
also some genes, such as pbgP and ugd, that were directly regulated in one species, but
indirectly regulated in the other; the overall regulatory logic for these genes was thus
conserved, but the precise mechanism has changed. Despite these examples, the vast
Capra 132
A
Yersinia pestis
Salmonella enterica
FWD]
WE
B
B
126
B
C
Salmonella bongoi
Escherichiacoli
Chromosome:
srfN promoter sequence
TCTG --- TTTTTTTTAGAAAAAAAAGTCTAT
Salmonella enterica Enteritidis - ACTGAAAAATTAT
-TGAAAAGTTCAT
Salmonella enterica Typhi ACTGAAAAEATTAG-T
CAT
Salmonella bongori
Salmonella enterica
Salmonella enterica Typhimurium ACTGAAAAATTATTTAG;A-TAAAAGTTCAT
SPI-2:
Chromosome,
Co
Acquisition of SPI-2
by lateral transfer
so
SsrB footprint
i
Figure 1.4 Evolution of transcriptional circuits controlled by two-component
pathways.
(A) Examples of genes directly regulated by the two-component pathway PhoQ-PhoP in
Salmonella enterica and Yersinia pestis. slyB is conserved and directly regulated by PhoP in both
species. rstA and psiE are conserved but directly regulated by PhoP in only one of the two
species. ugtL and y4126 are directly regulated and are unique to S. enterica and Y. pesis,
respectively. (B) Schematic of the Salmonella bongori and S. enterica chromosomes, each
harboring a srfN ortholog. The horizontally acquired SpiR-SsrB system, encoded on Salmonella
pathogenicity island 2 (SPI-2) in S. enterica but not S. bongori, evolved to transcriptionally
activate srfN. (C) De novo evolution of a response regulator-binding site. SPI-2 encodes the twocomponent pathway SpiR-SsrB, which was acquired after the divergence of S. enterica from S.
bongori. The gene srdN, ancestral to the Salmonella lineage, accumulated promoter mutations
that enabled activation by SsrB, a transcriptional link that contributes to Salmonella virulence. The
relevant portion of the srfN prmoter is shown with conserved poisitions shaded gray and the
region bound by SsrB in S. enterica underlined.
majority of genes directly regulated by PhoP in each organism were not conserved.
Instead, transcriptional rewiring appears to have been prevalent since the divergence of
Salmonella and Yersinia, leading to the gain and loss of PhoP-regulated genes in each
species (Figure 1.4A). It is tempting to speculate that these changes have tailored the
response of each species to magnesium limitation.
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Notably, the change in PhoP regulons between Salmonella and Yersinia may not always
result from a simple gain or loss of PhoP binding sites. In some cases, regulon differences
may reflect changes in (i) the orientation of, and distance between, a PhoP binding site
and the transcriptional start site and (ii) concomitant changes in how PhoP recruits RNA
polymerase. For instance, the PhoP binding site in the promoter of mgtC in Yersinia is
located in a position and orientation that enables gene activation by Yersinia PhoP, but
not by Salmonella PhoP, even though Salmonella PhoP can bind the mgtC promoter
(Perez and Groisman, 2009b). The ability to change the targets of a response regulator
without necessarily changing DNA-binding sites is also seen in Desulfovibrio, in which
two recently duplicated response regulators share DNA-binding motifs but regulate nonoverlapping target genes (Rajeev et al., 2011). Point mutations in OmpR have also been
identified that allow it to activate the kdpABC operon, usually activated by KdpE, not by
changing DNA binding but by changing the ability to interact with RNA polymerase
while bound to the promoter (Ohashi et al., 2005). Thus with a single point mutation, and
without any changes needed in the promoters of target genes, a duplicated response
regulator can regulate a new set of target genes. Collectively, these studies demonstrate
that two-component pathway outputs can evolve through changes in the DNA-binding
sites of response regulators or through changes in how response regulators interact with
RNA polymerase. They also highlight the critical need to couple computational analyses
of binding sites with experimental studies to reveal the functional and evolutionary
consequences of binding site conservation or loss.
Changes in response regulator outputs may also frequently occur after duplication or
lateral transfer events. After gene duplication, a change in the output response of one or
Capra 134
both regulators is likely a critical step in the establishment of new functions and,
consequently, the maintenance of the duplicated proteins. For instance, in E. coli, a
duplication event likely gave rise to the paralogous systems NarX-NarL and NarQ-NarP
which respond to nitrate and nitrite in anaerobic conditions (Rabin and Stewart, 1993).
While the regulators NarP and NarL share significant similarity and even recognize
highly similar consensus binding sites, divergent evolution has enabled each response
regulator to recognize different promoter architectures and to activate different genes
(Price et al., 2008). The duplication of the Nar two-component system has thus led to an
increase in complexity of the transcriptional control of genes necessary for growth in
anaerobic conditions.
The evolution of response regulator outputs in response to lateral gene transfer has also
been recently explored. A particularly illuminating example comes from studies of
Salmonella pathogenicity island-2 (SPI-2), which encodes a two-component signaling
system called SpiR-SsrB (Figure 1.4B-C). In addition to regulating the expression of
other SPI-2-encoded genes, the response regulator SsrB directly regulates the expression
of genes outside SPI-2 (Worley et al., 2000), indicating that SsrB-binding sites probably
evolved de novo within the promoters of these genes. This hypothesis was tested by
examining the evolution of a Salmonella gene, sr/N (Osborne et al., 2009). This gene is
ancestral to the Salmonella lineage and present in both S. enterica and S. bongori. By
contrast, SPI-2 and SsrB are found in S. enterica but not S. bongori (Figure 1.4B). A
comparison of the cis-regulatory regions of srJN indicated that the binding site for SsrB
was not present in S. bongori meaning it likely arose in the lineage leading to S. enterica
(Figure 1.4C). Importantly, this recruitment of an ancestral gene into the regulon of a
Capra 35
horizontally-acquired response regulator provided S. enterica with an adaptive advantage
as a pathogen. When the promoter of S. enterica srJN was replaced with that found in S.
bongori, cells were rendered significantly less virulent compared to the wild-type.
Conversely, the genes encoded on SPI-2 have evolved to be regulated by ancestral twocomponent pathways. A case in point is the expression of ssrB and spiR, which are
themselves regulated by OmpR and PhoP, two response regulators found throughout the
Gammaproteobacteria(Bijlsma and Groisman, 2005; Lee et al., 2000). By controlling
spiR and ssrB, these ancestral regulators likely help to ensure that virulence genes are
maximally expressed when Salmonella enters host cells. For instance, the PhoQ-PhoP
system is activated by the low-magnesium conditions that Salmonella experiences inside
host macrophages; the consequent activation of ssrB and spiR would then drive the
expression of virulence genes.
Although this introduction includes only a few cases, it is clear that response regulator
outputs can, and do, change rapidly. The observed changes to transcriptional circuitry
observed suggest that bacteria are resilient to, and capable of, transcriptional rewiring
(Perez and Groisman, 2009a). This notion was tested systematically by artificially
rewiring transcriptional connections; promoters for 26 different sigma and transcription
factors (including some response regulators) were combined with the open reading
frames of 23 of these transcriptional regulators and introduced into E. coli cells on a highcopy plasmid (Isalan et al., 2008). Strikingly, over 95% of these constructs, many of
which led to substantial transcriptional rewiring, were tolerated, with little to no growth
defect under standard laboratory conditions. One implication of this study is that after a
new DNA-binding response regulator is introduced by gene duplication or lateral
Capra 136
transfer, there is time to "scan" different regulatory possibilities. A new combination that
yields even a slight benefit could then be selected and rapidly fixed in a population.
Finally, the evolvability of response regulators and their outputs may also benefit from
the fact that most prokaryotic transcription factors regulate only a few genes, either
directly or indirectly (Madan Babu and Teichmann, 2003), decreasing the number of
binding sites that would need to co-evolve with the DNA-binding domain of a response
regulator, thereby increasing the likelihood that they can change (Rajewsky et al., 2002).
Dimerization specificity
After duplication, the generation of new, functional, and insulated pathways requires
changes to the residues that mediate homodimerization of histidine kinases and response
regulators. To establish new and insulated pathways, substitutions are needed that
eliminate heterodimerization of the diverging paralogous proteins while maintaining the
ability to homodimerize.
Most, if not all, histidine kinases form homodimers in order to autophosphorylate. There
is almost no evidence of physiologically-relevant heterodimerization, with one exception
in Pseudomonas aeruginosa (Goodman et al., 2009), indicating that histidine kinases
must harbor a set of amino acids that enforce homodimerization. Many of these residues
are likely to reside in the DHp domain, although upstream domains, such as PAS and
HAMP domains, could also contribute to dimerization specificity and stability. To better
pinpoint the residues mediating specificity, one recent study looked for coevolving
residues in a set of more than 15,000 histidine kinase sequences (Ashenberg et al., 2011).
This approach revealed a small set of strongly coevolving residues that mapped primarily
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to the DHp domain and mostly within the lower half of the four-helix bundle (Figure
1.5). Homodimerization specificity could be changed through directed mutagenesis of
these residues (Ashenberg et al., 2011).
Nearly 50% of response regulators, including all members of the OmpR family (Gao and
Stock, 2010), also form homodimers upon phosphorylation. Homodimerization is often
crucial for producing an output response as many response regulators have DNA-binding
domains and recognize tandem or inverted repeat elements within target promoters. A
systematic study of the 17 OmpR-family response regulators from E. coli demonstrated
that essentially all of them specifically homodimerize (Gao et al., 2008). Although
intermolecular interactions on the dimer interface involves highly conserved residues
within the receiver domain, some interfacial residues do vary, perhaps providing a
mechanism for ensuring homodimerization and excluding heterodimerization (ToroRoman et al., 2005). As with kinase dimerization amino acid coevolution studies have
identified a subset of interfacial residues that may help enforce homodimerization and
prevent heterodimerization (Weigt et al., 2009). These residues are likely to change
following gene duplication as a means of insulating paralogous response regulators from
one another, thereby enabling distinct outputs to result from the phosphorylation of each
regulator.
Evolution of phosphotransfer specificity and the insulation of pathways
The flow of information through two-component signaling pathways depends critically
on the transfer of phosphoryl groups from a histidine kinase to its cognate response
regulator. Despite early suggestions of rampant cross-talk, there is little evidence for such
Capra 138
-
1-1
A
TM0853 (HK)
4;
B
HK
HK-RR coevolving
residues
TM468 (RR)
I
HK-HK coevolving
residues
-
HK-RR coevolving
residues
EnvZ
RstB
CpxA
TMO853
230
240
250
AGVKQLADDRTLLMAGVS DLRTPLI
DNINALIASKKQLIDGIA LRTPLU
TALERMMTSQQRLLSDIS LRTPLU
ERLKRIDRMKTEFIANISULRTPLU
OmpR
RstA
CpxR
TMO468
10
20
30
40
50
60
70
MQENYKIL
LTEQGFQVRSVANAEQMDRLLTRESFHLMvL
GELSICRRL
--- NTIVFV
SI
LAKHDMQVTVEPRGDQAEETILRENPDLVLL IML GK
ICRDL
--- MNKILLV
S
ULEMEGFNVIVAHDGEQALDLLDD-SIDLLLLEM
IDTLKAL
DKK
-- MSKKVLLVAU R
SE
LKKEGYEVIEAENGIALEKLSEFTPDLIVL
FTVLKKL
C
RR
OmpR
Rs tA
CpxR
TMO468
11111111 -
260
270
280
290
MSEQ--------DGYLAES
KDIEECNAIIEQFIDYLRTG---QEM
SDNL--------SAAESQA4RDISQLEALIEELLTYARLDRPQNEL
LRRR------SGESKELERI TEAQRLDSMINDLLVMSRNQQ-KNAL
IYNSLGELDLSTLKEFLEVI DQSNHLENLLNELLDFSRLERKSLQI
11 111
80
90
100
RSQS--NPMPIIM
GEEVDRIVGLEI DDYIP
RAKW---SGPIVL
SLDSDMNHILALE
CDYIL
RQTH---QTPVIMIAGSELDRVLGLELIADDYLP
QEKEEWKRIPVIV
GGEEDESLALS
KVMU
-
04-
110
120
PRELLARIRAVLRRQAN
PAVLLARLRLHLRNEQ
DRELVARIRAILRRSHW
PSQFIEEVKHLLNE
W= highly conserved residues
S=
HK-RR coevolving residues
HK-HK coevolving residues
Figure 1.5 Amino acid coevolution in two-component signaling proteins.
(A) Residues that coevolve in cognate pairs of histidine kinases (HKs) and response regulators
(RRs) are shown with space-filling on the crystal structure of the Thermotoga maritima kinase
TM0853 bound to its cognate response regulator TM0468. Only the DHp domain of the kinase
and the receiver domain of the response regulator are shown. The histidine and the asparate that
are involved in phosphotransfer are shown as sticks in purple. Residues in histidine kinases that
coevolve strongly with other kinase residues are shown in cyan, while residues on the kinase that
coevolve with those on the response regulator are shown in orange and red respectively. (B-C)
coevolving residues from panel A are shown on (B) a sequence alignment of TM053 with three
Escherichia coli kinases, EnvZ, RstB, and CpxA, and (C) an alignment of TM0468 with three E.
coli regulators, OmpR, RstA, and CpxR. Secondary structure elements are indicated beneath the
primary sequence.
promiscuity in vivo with most kinases having one response regulator substrate or, on
occasion, two or three (Laub and Goulian, 2007; Skerker et al., 2005; Yamamoto et al.,
2005). This in vivo preference is mirrored in vitro, with histidine kinases harboring a
strong kinetic preference for phosphotransfer to their in vivo partner. For example, a
systematic, global study of phosphotransfer from E. coli EnvZ to each of the 32 response
Capra 139
regulators in E. coli demonstrated that OmpR was the preferred substrate. EnvZ
transferred to other substrates only after extended incubation times (Skerker et al., 2005).
These in vitro studies demonstrate that the specificity of two-component signaling
pathways is based primarily on molecular recognition rather than reliance on scaffolds or
other cellular strategies. This observation further suggests that the information necessary
for promoting the "correct", or desired, interaction and preventing "incorrect" interactions
is encoded at the sequence level (Skerker et al., 2008).
A consequence of relying on molecular recognition for specificity is that, during the
course of evolution, any mutation in a residue contributing to a kinase-regulator
interaction may disrupt signaling and place cells at a strong fitness disadvantage. Survival
would then depend on reversion of the mutation or a compensatory mutation in the
partner protein. Consistently, computational analyses of large sets of cognate kinaseregulator pairs have revealed extensive amino acid coevolution (Burger and van
Nimwegen, 2008; Skerker et al., 2008; Weigt et al., 2009). Conspicuously, the most
significantly coevolving pairs of residues map to the molecular interface formed during
phosphotransfer (Casino et al., 2009) suggesting they mediate the specificity of this
protein-protein
interaction (Figure 1.5). These residues, which have been called
specificity residues, map to the same region of the DHp domain that is also responsible
for homodimerization specificity. These specificity residues that dictate partnering
specificity are on the solvent exposed region of the cc-helix, while the dimerization
specificity residues are buried within the four-helix bundle. Using F. coli EnvZ as a
model kinase, a subset of these residues was shown to be sufficient, when mutated, to
reprogram substrate specificity both in vitro and in vivo (Skerker et al., 2008). For
Capra 140
example, mutating as few as three residues in EnvZ to match those found at equivalent
positions in RstB led EnvZ to preferentially phosphorylate RstA instead of OmpR (Figure
1.5A-B). Similarly, the response regulator CheY from Rhodobacter sphaeroides, has
been rationally rewired to interact with non-cognate kinases by mutating the coevolving,
specificity-determining residues (Bell et al., 2010). Directed evolution has also been used
to rewire two-component specificity. For example, mutants of the E. coli kinase CpxA
that phosphorylate and dephosphorylate OmpR were selected; many of the mutated
residues were also identified in the studies of kinase-regulator coevolution (Siryaporn et
al., 2010).
Another mechanism that may be used to enforce the specificity between cognate kinases
and response regulators is the use of alternative phosphotransfer mechanisms. Originally,
histidine kinases were thought to autophosphorylate in trans-i.e.the CA domain of one
homodimer phosphorylates the histidine in the DHp domain of the alternate homodimer
(Yang and Inouye, 1991). Recent crystallization studies have shown, however, that some
histidine kinases autophosphorylate in cis (Casino et al., 2009). This cis vs. trans
autophosphorylation mechanism has been attributed to the loop between a-helix- I and ahelix-2 of the DHp domain (Ashenberg et al., 2013), the same region that was also found
to be important for switching the phosphotransfer specificity of some kinases (Skerker et
al., 2008). Intriguingly, the histidine kinases for which both the specificity residues and
the loop need to be introduced into EnvZ in order to switch phosphotransfer specificity
include those kinases that are known to phosphorylate in cis. The slightly different
contacts made between the response regulator and the DHp domain of a kinase that
Capra 141
A
Histidine Kinase
H-0
Ancestral
QD
Response Regulator
I-(
Postduplication
(:D-.Z
Derived
SDJ
B
0ceier
nv
domain only
0o
Omp/
winged helix-turn-helix
NtrC/AAA+ and
FIS domains
60
oNarLI
GerE helix-turn-helix
Figure 1.6 Insulation of two-component pathways following gene duplication.
(A) Schematic of major steps in the insulation of two pathways following a duplication event. The
duplication of an ancestral pathway initially produces two identical pathways that cross-talk at the
level of phosphotransfer. Through the accumulation of mutations in specificity-determining
residues, the two pathways can become insulated. A similar process must occur, but is not
shown, at the levels of kinase and regulator homodimerization. (B) Schematic summarizing the
distribution of histidine kinase sequence space defined by their specificity-determining residues.
Each sphere represents the set of response regulators that a given kinase phosphorylates. This
set will include, but is not limited to, the cognate response regulator. With the exception of NarQ
and NarX, these spheres are presented as nonoverlapping to reflect the minimal cross-talk
between pathways. The relative positions of the spheres are based on the ability of individual
kinases to phosphorylate non-cognate response regulators after extended times in vitro (Skerker
et al., 2005; Yamamoto et al., 2005, unpublished data). Positions are approximate, and a twodimensional representation of a multidimensional sequence space. The diagram is intended to
convey a general sense of how kinases are distributed in sequence space. Spheres are colored
according to the subfamily of each kinase's cognate response regulator. Spheres with dashed
outlines indicate kinases for which no data exist to infer relative positions. Hybrid histidine
Capra 142
kinases, which are under different selective pressures, are excluded.
autophosphorylates in cis or in trans, may help to enforce phosphotransfer specificity,
particularly after a duplication event.
Although specificity-determining residues do coevolve, these correlated changes appear
to be rare events as the specificity residues of many kinase-regulator systems are nearly
invariant over relatively long timescales. So when and why do specificity residues change
and coevolve? One strong possibility is that substitutions occur following gene
duplication, helping to insulate the duplicate kinase-regulator pairs from each other
(Figure 6A). That is, a series of mutations presumably must occur to prevent cross-talk
between two duplicated pathways, while maintaining the interaction within each pair.
Such an accumulation of changes in specificity residues, however, is inherently risky
business for a bacterium. Due to large population sizes, even slightly deleterious
mutations are likely to be quickly removed from the population. Hence, for a new kinaseregulator pair to be maintained in the genome, the mutational intermediates between its
initial state and its final, insulated state must be neutral, or nearly neutral. In other words,
cognate kinase-regulator pairs must retain their ability to interact as the specificity
residues coevolve and find a region of sequence space in which they are insulated from
other two-component proteins within the cell. This may be one reason that hybrid kinases
are overrepresented among recent gene duplications (Ahn et al., 2006). Similarly, after a
lateral gene transfer event involving two-component signaling genes, the newly
introduced kinase-regulator pair may need to accumulate substitutions in phosphotransfer
Capra 143
specificity residues to avoid cross-talk with existing systems, thereby maintaining the
fidelity of information flow within the cell.
The notion of insulation, or orthogonality, in sequence space can be extended from
individual, recently duplicated pairs of signaling proteins to the entire complement of
two-component signaling proteins in a given organism. For example, all 29 histidine
kinases in E. coli ultimately arose through some combination of gene duplication and
lateral transfer. The net result is a system of signaling pathways that are, with a few
exceptions, insulated from one another in sequence space and with respect to
phosphotransfer, as observed by global phosphotransfer profiling (Figure 1.6B). This
system-wide insulation suggests that negative selection and the avoidance of cross-talk
are powerful forces influencing the evolution of two-component signaling proteins.
Negative selection has been suggested to influence other paralogous signaling protein
families, such as SH3-domain-containing proteins found in eukaryotes (Zarrinpar et al.,
2003). Two notable exceptions to the orthogonality of phosphotransfer specificity in E.
coli are the kinases NarQ and NarX, which share significant similarity in terms of
phosphotransfer specificity residues and, consistently, both phosphorylate the response
regulators NarL and NarP, although with different kinetic preferences (Noriega et al.,
2010). Other exceptions to the orthogonality of specificity residues include hybrid
histidine kinases, which phosphotransfer intramolecularly to an attached receiver domain.
This spatial arrangement may enforce the specificity of phosphotransfer in hybrid kinases
and, consequently, their specificity-determining residues may not be under the same
pressure to avoid cross-talk with other two-component pathways.
Capra 144
Research approach
I sought to investigate the evolutionary pressures that act on the interaction between
histidine kinases and response regulators. In chapter two, I begin by asking what
mutational trajectories can two-component proteins follow after a duplication event in
order to insulate the two new pathways? And, in particular, how do duplicated proteins
move through the sequence space defined by the specificity-determining residues of
histidine kinases and response regulators? Answering these questions through sequence
analysis is problematic because transient intermediates may not be captured in extant
sequences and the behavior of ancestral or intermediate states is difficult to infer from
sequence alone. To circumvent these issues, I experimentally examined all possible
specificity intermediates between the two E. coli kinases EnvZ and RstB and
demonstrated that a cognate kinase-regulator pair can, in fact, move in sequence space
from the region occupied by EnvZ-OmpR to that occupied by RstB-RstA while (i)
introducing only one mutation at a time, (ii) maintaining the interaction between the
kinase and the regulator and (iii) avoiding to introduction of cross-talk to other closely
related pathways such as CpxA-CpxR. Notably though, only a small fraction of all
possible mutational trajectories satisfy these criteria, indicating that the evolution of
signaling proteins post-duplication may be fundamentally constrained.
In chapter three I focus on identifying the evolutionary forces driving the evolution of
specificity residues. I showed that in the Alphaproteobacteria, NtrB/NtrC likely
duplicated to produce NtrB/NtrC and NtrX/NtrY. Subsequent divergence of NtrX/NtrY
to insulate the duplicated pathways likely lead to the overlap of NtrX/NtrY sequence
space with that already occupied by PhoR/PhoB. In order to resolve the cross-talk, the
Capra 45
specificity residues of PhoR/PhoB evolved specifically in the Alphaproteobacteria. I
demonstrated that in the absence of duplication, specificity residues remain remarkably
conserved between orthologous histidine kinases. Duplication of a two-component
system can introduce cross-talk with pre-existing two-component systems within the cell.
This cross-talk provides a strong selective disadvantage in vivo, resulting in rapid
diversification of specificity residues until insulation of two-component systems is
achieved.
In chapter four, I shifted my focus from canonical kinases to hybrid kinases.
As
described above, hybrid kinases are comprised of a histidine kinase that is covalently
attached to its cognate receiver domain. Although they comprise nearly 25% of all
histidine kinases, they remain less well studied and, unlike canonical two-component
systems, the interactions between
the kinase and the receiver domain remain
incompletely understood. I employed the same approach of covariation to identify
specificity residues that are responsible for determining interactions between the histidine
kinase and the receiver domain of hybrid kinases and demonstrated that, as expected,
their specificity residues are not under the same evolutionary pressure to diverge postduplication. I showed that after duplication, the pressure for specificity residues to
diverge is weaker; the high effective concentration of the covalently attached receiver
domain acts to prevent cross-talk with other two component systems within the cell.
Surprisingly, however, the specificity residues of a hybrid kinase are still important in
order to allow a histidine kinase to interact with its cognate, covalently attached, receiver
domain. Only kinases and receiver domains that are able to interact in vitro when
separated are able to interact when covalently attached. Thus covalent attachment of a
Capra 146
receiver domain serves primarily to prevent cross-talk, not to increase cognate
interactions.
In chapter five, I review the conclusions and implications of the work. I also outline the
remaining questions, including understanding the size, shape, and distribution of
sequence space and the evolution of input and output responses after duplication. In
addition, one large unanswered question involves the ubiquity of certain DNA binding
domains. Similarly to how I have explored the mechanisms by which cells can coordinate
a large number of two-component pathways even given their high sequence and structural
homology, most organisms also encode a large number of highly similar response
regulators containing homologous DNA-binding domains. I outline several important
questions and approaches that can be used in order to understand specificity in the
response
regulator-DNA-binding
interaction,
and
approaches
to
elucidate
the
mechanisms by which two-component systems can be insulated on the transcriptional, or
output, level.
Capra 147
Acknowledgements
Support was provided by the National Institutes of Health and the National Science
Foundation. M.T.L is an Early Career Scientist at the Howard Hughes Medical Institute.
Capra 148
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Capra 156
Chapter 2
Systematic dissection and trajectory-scanning mutagenesis of
the molecular interface that ensures specificity of twocomponent signaling pathways
This work was published as Emily J. Capra*, Barrett S. Perchuk*, Emma A. Lubin, Orr
Ashenberg, Jeffrey M. Skerker, and Michael T. Laub. 2010. PLoS Genet. Nov 24;6(11):
e1001220
EJC, BSP, JMS, and MTL conceived and designed the experiments. EJC and BSP performed the
experiments. EAL contributed reagents. OA performed the computational analysis. EJC and MTL
wrote the paper. EJC and BSP contributed equally to the work.
Capra 157
Abstract
Two-component signal transduction systems enable bacteria to sense and respond to a
wide range of environmental stimuli. Sensor histidine kinases transmit signals to their
cognate response regulators via phosphorylation.
The faithful transmission of
information through two-component pathways and the avoidance of unwanted cross-talk
requires exquisite specificity of histidine kinase-response regulator interactions to ensure
that cells mount the appropriate response to external signals.
To identify putative
specificity-determining residues we have analyzed amino acid coevolution in twocomponent proteins and identified a set of residues that can be used to rationally rewire a
model signaling pathway, EnvZ-OmpR. To explore how a relatively small set of residues
can dictate partner selectivity, we combined alanine-scanning mutagenesis with an
approach we call trajectory-scanning mutagenesis, in which all mutational intermediates
between the specificity residues of EnvZ and another kinase, RstB, were systematically
examined for phosphotransfer specificity. The same approach was used for the response
regulators OmpR and RstA.
Collectively, the results begin to reveal the molecular
mechanism by which a small set of amino acids enables an individual kinase to
discriminate amongst a large set of highly-related response regulators and vice versa.
Our results also suggest that the mutational trajectories taken by two-component
signaling proteins following gene or pathway duplication may be constrained and subject
to differential selective pressures. Only some trajectories allow both the maintenance of
phosphotransfer and the avoidance of unwanted cross-talk.
Capra 158
Author Summary
Maintaining the specificity of signal transduction pathways is critical to the ability of
cells to process information, make decisions, and regulate their behavior. Preventing
cross-talk often relies predominantly on molecular recognition and a set of specificitydetermining residues in cognate proteins. Identifying these residues and understanding
how they dictate specificity is still a major challenge. Additionally, we have a
rudimentary understanding of how specificity evolves, particularly after gene duplication
events. We tackled these questions using two-component signaling proteins, the largest
family of bacterial signaling proteins. Using analyses of amino acid coevolution, we
pinpointed a set of specificity residues in histidine kinases and their cognate substrates.
Then, using systematic mutagenesis we characterized the complete set of intermediates
between two different signaling systems, EnvZ/OmpR and RstA/RstB.
The results
demonstrate that specificity residues contribute unequally and, importantly, that some
residues depend substantially on the identity of neighboring residues.
We also
demonstrate how the specificity of EnvZ/OmpR can be reprogrammed to match that of
RstB/RstA
through
a series of individual
substitutions without disrupting the
kinase/regulator interaction. Notably, this property is not shared by all trajectories from
EnvZ/OmpR to RstA/RstB, suggesting that the duplication/divergence process that likely
produced these two pathways may have been fundamentally constrained.
Capra 159
Introduction
Protein-protein interactions are crucial to virtually every cellular process.
Within the
crowded confines of the cell, proteins must distinguish between their cognate partners
and non-cognate partners, in order to avoid unproductive and potentially deleterious
interactions. The problem of interaction specificity is particularly acute for paralogous
protein families where proteins with diverse cellular functions share significant structural
and sequence similarity. Cells have evolved many mechanisms to cope with potential
cross-talk and to ensure the specificity of protein-protein interactions (Schwartz and
Madhani, 2004; Ubersax and Ferrell, 2007). In multicellular organisms, spatial
mechanisms that prevent related, but distinct, proteins from coming in contact with one
another are often used to create specificity. For example, scaffold proteins, the
localization of proteins to different subcellular compartments, and tissue-specific
expression can all insulate distinct pathways. Temporal mechanisms, such as the
differential timing of expression, are also used to insulate pathways.
Although cells
employ each of these strategies, in many cases the primary means of preventing
unwanted interactions is molecular recognition. However, our understanding of precisely
how proteins discriminate between cognate and non-cognate partners at the molecular
level is surprisingly rudimentary. Identifying the amino acids responsible, elucidating the
precise roles played by each residue, and understanding their complex interdependencies
remain major challenges for most protein-protein interactions.
Two component signal transduction pathways provide a tractable system for addressing
these questions. These signaling pathways, which are the dominant form of signaling in
bacteria, typically consist of a sensor histidine kinase (HK) and a cognate response
regulator (RR) (Stock et al., 2000). Upon activation of the pathway, a histidine kinase
dimer will autophosphorylate on a conserved histidine that then serves as the
phosphodonor for a cognate response regulator. Phosphorylation of the response
Capra 60
regulator typically activates an output domain which can effect changes in cellular
physiology, often by modulating gene expression (Gao et al., 2007).
Many histidine
kinases are bifunctional and when not active for autophosphorylation, will drive the
dephosphorylation of their cognate response regulators.
Two-component signaling systems are used for sensing and adapting to a wide range of
environmental and intracellular stimuli (Stock et al., 2000) and most bacterial species
encode dozens, if not hundreds of kinase-regulator pairs. Most histidine kinases have
only one or two cognate response regulators, and there is minimal cross-talk between
different pathways at the level of phosphotransfer (Laub and Goulian, 2007; Skerker et
al., 2005). The specificity of phosphotransfer is dictated, on a system-wide level, at the
level of molecular recognition (Skerker et al., 2005). That is, histidine kinases exhibit a
large kinetic preference in vitro for their in vivo cognate regulator(s) relative to all other
response regulators (Fisher et al., 1996; Grimshaw et al., 1998; Skerker et al., 2005).
Hence, cellular context is not essential and the basis of in vivo phosphotransfer specificity
can be dissected in vitro.
To identify the amino acids that govern the specificity of phosphotransfer in twocomponent pathways, several groups have examined patterns of amino acid coevolution
in cognate pairs of histidine kinases and response regulators (Burger and van Nimwegen,
2008; Skerker et al., 2008; Weigt et al., 2009; White et al., 2007). The rationale behind
this approach is that if a residue critical to molecular recognition mutates, it must either
revert or be compensated for by a mutation in the cognate protein. Many of the residues
identified in these computational approaches are at the molecular interface formed in a
co-crystal structure of a histidine kinase-response regulator complex (Casino et al., 2009).
However, residues in direct contact do not necessarily dictate specificity (Skerker et al.,
2008) and computational approaches alone cannot reveal how a histidine kinase
discriminates between cognate and non-cognate substrates.
Capra 161
Using the E. coli histidine kinase EnvZ as a model, we mapped a subset of coevolving
residues that are critical to the specificity of phosphotransfer (Skerker et al., 2008).
Mutating as few as three residues within the DHp (Dimerization and Histidine
phosphotransfer) domain of EnvZ was sufficient to reprogram its phosphotransfer
specificity from OmpR to the non-cognate substrate RstA. Although a set of residues that
could switch the phosphotransfer specificity of EnvZ was identified, several fundamental
questions remain unanswered.
Can phosphotransfer specificity also be rewired by
making mutations in a response regulator? Do individual specificity residues function as
positive elements to promote cognate interactions, as negative elements to prevent noncognate interactions,
or both?
Do individual residues contribute
equally and
independently or are there "hot spots" and dependencies at the amino acid level?
Here, we couple analysis of amino acid coevolution with alanine-scanning mutagenesis
and an approach we call trajectory-scanning mutagenesis to systematically dissect the
basis of phosphotransfer specificity in two-component signaling pathways. The results
provide new insights into how histidine kinases use a set of amino acids to "choose" their
cognate substrates, and vice versa. The results have important implications for
understanding the evolution of two-component signaling pathways and the mechanisms
that cells can use to insulate pathways following gene duplication.
Capra 162
Results
Identification of coevolving residues in cognate kinase-regulator pairs
To identify the amino acids responsible for determining the specificity of phosphotransfer
in two-component signaling pathways, we searched for residues that covary in cognate
HK-RR pairs. Histidine kinases and response regulators that are encoded in the same
operon typically form exclusive one-to-one pairings, exhibiting a highly specific
interaction both in vivo and in vitro. We identified ~4500 operonic pairs of histidine
kinases and response regulators from a phylogenetically diverse set of 400 sequenced
bacterial genomes. To identify coevolving residues, we concatenated cognate HK-RR
pairs, performed a large multiple sequence alignment, and then measured mutual
information between columns of the sequence alignment. We noted that some columns
tended to have high mutual information scores with many other columns in the
alignment, an observation also made in other analyses of mutual information (Gloor et
al., 2005). For example, positions 8 and 270 have relatively broad score distributions with
long tails, while positions 18 and 202 have narrower distributions centered closer to the
origin (Figure 2.1A-B).
Consequently, the pairs 8-270 and 18-202, which possess
identical mutual information scores of 0.35, cannot be treated identically. We used a
relatively simple correction in which raw MI scores were normalized by each column's
average raw MI score with all 310 positions in the sequence alignment (Figure 2.1 C).
At an adjusted score threshold of 3.5, we found 12 coevolving pairs, comprising 9
residues in the histidine kinases and 7 in the response regulators (Figure 2.2A-C). These
residues form a single, densely-interconnected cluster of coevolving residues. The
Capra 163
A
position 8
C
position 270
7
6
60
0
Lb
0
20
LLJ
0.2
0.4
-E
...
....
. .........
..'
*.
.....
.
3
2
8
-
0.6
0
0.4
0.2
MI
0.6
MI
-2
0
0.1
0.3
0.2
0.4
raw MI
position 202
position 18
B
4
601
e
a.
4U
0
202
20
0
0
18
1.
0.2
0.4
MI
0.6
0
0.2
J
0.4
0.6
MI
Figure 2.1 Adjusted mutual information analysis of amino acid covariation in twocomponent proteins.
(A) Histograms summarizing the raw mutual information scores for columns 8 and 270 in the
kinase-regulator alignment. The arrow indicates the location of the score for the column pair 8270. (B) Same as panel A, but for positions 18 and 202 in the alignment. (C) Scatterplot of raw
mutual information scores against adjusted mutual information scores, as described in the main
text and in Materials and Methods. Dashed line indicates the score cutoff of 3.5 used in Figure
2.2.
Residues are all solvent-exposed in the individual molecules, but buried within the
molecular interface formed in a co-crystal structure of T. maritima HK853 and RR468
(Figure 2.2D) (Casino et al., 2009). The residues identified here overlap substantially
with, but are not identical to, those we identified previously (Skerker et al., 2008). Of the
coevolving residues in the kinase, all are in the DHp domain, consistent with this domain
being the primary site of interaction with the response regulator.
Within the DHp
domain, the coevolving residues are found on both alpha helices and are located below
the histidine phosphorylation site (Figure 2.2D). The covarying residues in the response
regulator are spatially near the conserved aspartic acid phosphorylation site (Figure
Capra 164
D
A
MI score > 3.5
RR
HK853
B
HK
RR468
270
260
SEQ--------DGYLAESIN
SDNL--------SAAESQ L
TLRRR------SGESKELE3
L
IYNSLGELDLSTLKEFLEII
280
290
EnvZ
RstB
CpxA
HK853
230
240
250
AGVKQLADDRTLLMAGVS LRTPL
L
DNINALIASKKQLIDGI
LRTP
L
TALERMMTSQQRLLSDIS LRTP
ERLKRIDRMKTEFIANI
LRTPL3I .
EnvZ
330
340
320
300
310
PMEMADLNAVLG----EVIAAESGYEREIETALYP-GSIEVKMHPLSIKRAV
RstB
CpxA
HK853
HLSEPDLPLWLSTHLADIQAVTPDKTVRIKTLVQG-HYAALDMR--LMERVL LLNLRYCHST-----VETSLLLSGN
IVRILRYSHTK-----IEVGFAVDKD
VSETIKANQLWSEVLDNAAFEAEQMGKSLTVNFPP-GPWPLYGNPNALESALE
LLNGVKYSKKDAPDKYVKVILDEKDG
NREKVDLCDLVESAVNAIKEFASSHNVNVLFESNVPCPVEAYIDPTRIRQVL
EnvZ
RstB
CpxA
HK853
400
370
380
390
QPFVRGDSAR--TIS
RAWFQVERGFfI APEQRKH
IAPENREHIEPFVRLDPSRDRSTG
RATLIVEIP
GITITVII PISPEDREQI RPFYRTDEARDRESG
PDHAKDR EQFYRVDSSLTYEVP
GVLIIVE N 1
OmpR
RstA
CpxR
RR468
20
10
MQENYKILVV
RK
--- MNTIVFVi
S I
S
--- MNKILLVi
-- MSKKVLLVAUR
C
RR
80
OmpR
RstA
CpxR
RR468
RSQS--NPMPIIMV
RAKW---SGPIVL
RQTH---QTPVIM
QEKEEWKRIPVIV
-=
i;5
I
ILA
IEECNAIIEQFIDYLRTG---QEM
ISQLEALIEELLTYARLDRPQNEL
AQRLDSMINDLLVMSRNQQ-KNAL
SNHLENLLNELLDFSRLERKSLQI
350
360
VVARYGNGW-----IKVSSGTEPN
440
450
420
430
410
IVQRIVDNHN MLELGTSERGGLSIRAWLPVPVTRAQGTTKEG
IVHSIALAMITVNCDTSELGGARFSFSWPLWHNIPQFTSA
IVETAIQQHR3VKAEDSPLGGLRLVIWLPLYKRS
ITKEIVELHGIRIWVESEVGKGSRFFVWIPKDRAGEDNRQDN
70
60
50
40
30
LTEQGFQVRSVANAEQMDRLLTRESFHLMVLSICRRL
TICRDL
LAKHDMQVTVEPRGDQAEETILRENPDLVL IM1GKI
I DTLKAL
LEMEGFNVIVAHDGEQALDLLDD-SIDLLL
FTVLKKL
LKKEGYEVIEAENGQIALEKLSEFTPDLIV
110
100
90
KGEEVDRIVGLEI
SLDSDMNHILALE
GSELDRVLGLE
AKGGEEDESLALS
-
DDYI PEI
CDYI
DDYLP
-
KVMR8
120
RELLARIRAVLRRQAN
PAVLLARLRLHLRQNEQ
DRELVARIRAILRRSHW
ON
=
highly conserved
residues
E=covaryingresidues
PSQFIEEVKHLLNE
-
Figure 2.2 Identification of coevolving amino acids in cognate pairs of histidine
kinases and response regulators.
(A) Residues in histidine kinases and response regulators that strongly coevolve (adjusted MI
score > 3.5) are listed with lines connecting covarying pairs. Residues are numbered according
to their position in E. coli EnvZ and OmpR. (B-C) Residues in histidine kinases that coevolve with
residues in response regulators are shown on a primary sequence alignment of HK853 from T.
maritima and EnvZ, RstB, and CpxA from E. coli. Residues in response regulators that strongly
coevolve with residues in histidine kinases are shown on a primary sequence alignment of RR468
from T. maritima and OmpR, RstA, and CpxR from E. coli. Residues highly conserved across all
two-component signaling proteins are shaded in grey. Coevolving residues are shown in orange
and red for the kinase and regulator, respectively. Secondary structure elements, based on the
co-crystal structure of HK853 and RR468 from T. maritima (Casino et al., 2009), are shown
beneath the sequences. (D) Coevolving residues mapped onto the HK853-RR468 structure.
Coevolving residues are shown by space-filling and colored as in panels A-C. The side chains of
the conserved phosphorylatable histidines and aspartate are shown as magenta sticks. The
HK853-RR468 complex is shown in the center with each individual molecule rotated 900 and
shown separately.
Capra 165
MI score> 3.0
A
D
HK
RR
91
RR468
HK853
B
HK
EnvZ
RstB
CpxA
HK853
230
240
AGVKQLAD
LLMAGVSJDL
DNINALIAS LIDGI EL
TALERMM TS RLLSDIS EL
ERLKRID
EFIANIS EL
EnvZ
RstB
CpxA
HK853
300
310
320
330
340
350
360
PMEMADLNAVLG----EVIAAESGYEREIETALYP-GSIEVKMHPLSIKRAVAMVVAA*GNGW-----IKVSSGTEPN
HLSEPDLPLWLSTHLADIQAVTPDKTVRIKTLVQG-HYAALDMR--LMERVL
LL
CHST-----VETSLLLSGN
VSETIKANQLWSEVLDNAAFEAEQMGKSLTVNFPP-GPWPLYGNPNALESAL
IVR
SHTK-----IEVGFAVDKD
NREKVDLCDLVESAVNAIKEFASSHNVNVLFESNVPCPVEAYIDPTRIRQVL LLLNOVUSKKDAPDKYVKVILDEKDG
EnvZ
RstB
CpxA
HK853
370
380
390
400
PIAPEQRKH QPFVSAR--TIS IIA
RAWFQVE
RATLIVE DIPIIAPENREH EP
PSRDRSTGCLW
GITITVDIDPOvSPEDREQ RPFY EARDRESG IRE
GVLIIVEbIIEPDHAKDREQFY
SLTYEVP IrL
C
250
P
LI
P
L
P L
P
I
-
260
270
S)-------- DGYLAES I
SDNL--------SAAESQ5L
LR-----SGESKELEII
IY SLGELDLSTLKEFLEII
t
280
290
IEECNAIIEQFIDYLRTG---QEM
ISQLEALIEELLTYARLDRPQNEL
AQRLDSMINDLLVMSRNQQ-KNAL
SNHLENLLNELLDFSRLERKSLQI
410
420
430
440
450
IVQRIVDNHNFLELGTSERGGLSIRAWLPVPVTRAQGTTKEG
IVHSIALAMGTVNCDTSELGGARFSFSWPLWHNIPQFTSA
IVETAIQQHR VKAEDSPLGGLRLVIWLPLYKRS
ITKEIELHG
IWVESEVGKGSRFFVWIPKDRAGEDNRQDN
-
ATP ld
70
30
40
50
60
LSICRRL
LTEQGFQVRSVANAEQMDRLLTRESFHLMvL
LAKHDMQVTVEPRGDQAEETILREPDLVLL IMGKU
TICRDL
LEMEGFNVIVAHDGEQALDLLDD-SIDLLLL M
NIDTLKAL
LKKEGYEVIEAENGQIALEKLSEFTPDLIVLIMIVtITVLKKL
RstA
CpxR
RR468
10
20
I
MQENYILV
--- MNTIVFV*4GS
--- MNKILL VPuSE
-- MSKKVLL
AR
OmpR
RstA
CpxR
RR468
120
100
110
80
90
PRELLARIRAVLRRQAN
RSQS--NPMPIIMV3AKGEEVDRIVGLEI ADDYI
RAKW---SGPIVLL SLDSDMNHILALE
CDYI
PAVLLARLRLHLRQNEQ
DDYL
DRELVARIRAILRRSHW
RQTH---QTPVIML3ARGSELDRVLGLE
RKVMUUPSQFIEEVKHLLNE
QEKEEWKRIPVIVLIAKGGEEDESLALS
OmpR
RR
-MP
-M0
-
-
-
0
-
-
2
high yconservedresidues
m covarying residues
-
Figure 2.3 Identification of coevolving amino acids in cognate pairs of histidine
kinases and response regulators.
Same as Figure 2.2, except at a score threshold of 3.0. (A) residues in histidine kinases and
response regulators that strongly coevolve (adjusted MI score > 3.0) are listed with lines
connecting covarying pairs. Residues are numbers according to their position in E. coli EnvZ and
OmpR and colored as in panels B-D. (B-C) Residues in histidine kinases that coevolve with
Capra 66
residues in response regulators are shown on a primary sequence alignment of HK853 from T.
maritima and EnvZ, RstB, and CpxA from E. coli. Residues highly conserved across all twocomponent signaling proteins are shaded in grey. Coevolving residues above and below the
phosphorylation site in the kinase are shown in green and orange, respectively. These two sets of
residues coevolve with residues in the response regulator shaded in yellow and red, respectively.
Secondary structure elements, based on the co-crystal structure of HK853 and RR468 from T.
maritima (Casino et al., 2009), are shown beneath the sequences. (D) Coevolving residues
mapped onto the HK853-RR458 structure. Coevolving residues are shown by space-filling and
colored as in panels A-C. The side chains of the conserved phosphorylatable histidines and
aspartate are shown as magenta sticks.
2.2D), predominantly on a single face of alpha helix-I in the receiver domain with one
additional residue within the p5-c5 loop. At lower score thresholds, an additional cluster
of coevolving residues are found (Figure 2.3), but we focus here on the set of 16 residues
identified at a threshold of 3.5.
Rewiring response regulator specificity
Our previous studies demonstrated that many of the coevolving residues in the kinase
(Figure 2.2) are critical to the phosphotransfer specificity of EnvZ and when mutated can
reprogram its substrate selectivity (Skerker et al., 2008). To test whether we could also
rewire the specificity of a response regulator, we again coupled our analyses of
coevolution with site-directed mutagenesis. We aimed to mutate the response regulator
OmpR such that it was no longer phosphorylated by its cognate kinase EnvZ and instead
was phosphorylated by the non-cognate kinase CpxA or RstB.
Each kinase was
autophosphorylated, purified away from unincorporated nucleotide, and tested for
phosphotransfer.
In our reaction conditions at a 1 minute time point, EnvZ
phosphotransfers exclusively to OmpR, whereas CpxA and RstB phosphotransfer
exclusively to CpxR and RstA, respectively (Figure 2.4).
Capra 167
OmpR(MI-RstA)
OmpR(MI+Ioop-RstA)
0
10
30
OmpR
(MI+loop-RstA)
OmpR
(MI-RstA)
OmpR
time (sec.)
OmpR(R15E,L16VR22A)
= OmpR(R15E,L16VR22A,P106T,F107T,N108P)
=
60
0
10
30
60
0
10
30
60
RstA
0
10
30
60
HK
EnvZ
HK D
RR
B
OmpR(MI-CpxR)
= OmpR(R15E,R22E,Y23L)
OmpR(MI+Ioop-RstA) = OmpR(R15E,R22E,Y23L,P109D)
OmpR
(MI-CpxR)
OmpR
time (sec.) 0
HK Do
10
30
60
0
10
30
60
OmpR
(MI+Ioop-CpxR)
0
10
30
60
CpxR
0
10
30
60
7
EnvZ
RR
HK D
CpxA
RR 0
Figure 2.4 Rewiring the specificity of response regulators.
(A) The histidine kinases EnvZ and RstB were autophosphorylated and examined for
phosphotransfer to the response regulators indicated. The mutations in OmpR(MI-RstA) and
OmpR(Ml+loop-RstA) are listed at the top. (B) The histidine kinases EnvZ and CpxA were
autophosphorylated and examined for phosphotransfer to the response regulators indicated. The
mutations in OmpR(MI-CpxR) and OmpR(Ml+loop-CpxR) are listed at the top. Each gel image
Bands corresponding to
shows phosphotransfer after 0, 10, 30, and 60 seconds.
If phosphotransfer occurred, bands
autophosphorylated kinases are labeled on the left.
corresponding to the phosphorylated regulator appear below the kinase band.
Capra 168
We first substituted residues in OmpR at the positions within alpha helix-I identified by
mutual information analysis with the corresponding residues from CpxR and RstA to
create OmpR(MI-CpxR) and OmpR(MI-RstA);
in each case three amino acid
substitutions were made in OmpR. The mutant OmpR(MI-RstA) was not phosphorylated
to a significant extent by RstB and was still a robust target of EnvZ (Figure 2.4A). The
mutant OmpR(MI-CpxR) showed diminished phosphotransfer from EnvZ and was now
phosphorylated by CpxA, although less efficiently than wild type CpxR (Figure 2.4B).
The residues in alpha helix- I are thus important for phosphotransfer specificity, but other
residues must contribute. We hypothesized that residues within the
@5-ca5
loop may also
affect specificity of the regulator. One of these residues covaried strongly with residues in
the histidine kinase (Figure 2.2) and other loop residues covaried at a slightly lower score
threshold of 2.8. We thus swapped the residues in the OmpR loop with those from CpxR
and RstA to create OmpR(MI+loop-RstA) and OmpR(MI+loop-CpxR), respectively, and
examined phosphotransfer to each of these constructs; the former required three amino
acid substitutions and the latter just one. Both constructs exhibited a nearly complete
switch in phosphotransfer specificity. EnvZ was unable to phosphotransfer to either
OmpR(MI+loop-RstA) or OmpR(MI+loop-CpxR), whereas phosphotransfer from RstB
or CpxA to the respective rewired OmpR mutants was efficient and at near wild-type
rates (Figure 2.4). Thus, the top coevolving residues appear sufficient, when mutated
along with the P5-a5 loop, to rewire the phosphotransfer specificity of OmpR.
We note that the residues mutated to change the specificity of OmpR constitute a subset
of the molecular interface formed by a cognate kinase and regulator (Figure 2.2D). For
instance, the residues in the P4-a4 loop of the response regulator contact the histidine
Capra I 69
kinase, are in close proximity to the top coevolving residues, and coevolve with sites in
the kinase at lower score thresholds (Figure 2.3), but mutating them was not required to
change phosphotransfer specificity (Figure 2.4). We conclude that the strongest
coevolving residues are necessary and sufficient to change the phosphotransfer partnering
specificity of OmpR. Other residues may fine-tune the interaction, but do not make
major contributions.
Alanine-scanning mutagenesis and the role of individual residues
Our results indicate that kinase-substrate interaction specificity in two-component
pathways is determined by a relatively small set of residues.
But does each residue
contribute equally to specificity or are there "hotspots" that contribute disproportionately?
Do individual residues help bind the cognate substrate or help prevent interaction with
non-cognate substrates?
To address these questions, we performed alanine-scanning
mutagenesis on the DHp domain of EnvZ. Surprisingly, despite being one of the bestcharacterized histidine kinases, EnvZ has never been explored through alanine-scanning
mutagenesis. One study described a series of cysteine mutants (Qin et al., 2003), but the
set of residues examined was limited and the interpretation of cysteine mutations can be
ambiguous. We created a series of 33 EnvZ mutants to probe the role of most of the
solvent-exposed residues in the DHp domain, generating alanine mutations for all
residues except for A255, which was substituted with a threonine (Figure 2.5A).
We first examined the autophosphorylation activity of each EnvZ mutant (Figure 2.5B,
2.6A). As expected, mutating the conserved phosphorylation site H243 (data not shown),
Capra 170
rn
phosphotransfer to RatA
(increase In RstA-P, relative to WT)
a
L230A
R234A
T235A
L236A
G240A
R246A
T247A
P248A
T250A
R251A
1252A
R253A
L254A
A25ST
T256A
C E257A
M258A
N. M259A
S260A
E261A
Q262A
D263A
G264A
S269A
K272A
D273A
E275A
E276A
E282A
Q283A
D286A
a
1252A
1252A
E261A
D263A
G264A
S269A
D263A
*26"
S269A
K272A
K272A
D273A
L254A
A255T
rn T256A
'C E257A
N M258A
C
L230A
R234A
T235A
L236A
G240A1
R246A
T247A
P248A
T250A
R251A
R253A
L254A
A255T
'C T256A
N E257A
C M258A
M259I
S260A
E261A
R253A
M259A
S260A
Q262A
D273A
E275A
E276A
E282A
Q283A
D286A
autophosphorylation (%WT)
decrease in EnvZ-P after
incubation with OmpR (%WT)
OmpR-P dephosphorylation rate (%WT)
L230A
R234A
T235A
L236A
G240A
R246A
T247A
P248A
T250A
R251A
w
0
a
Q262A
E275A
E276A
E282A
Q283A
D286A
L230A
R234A
T235A
L236A
G240A
D244A
R246A
T247A
P248A
L249A
T250A
R251A
1252A
-3,
n y
:9~10 n :
CnD x
U
LNI
R253A
L254A
m A255T
w
N~
T256A
N E257A
M258A
M259A
S2BOA
E261A
Q262A
D263A
G264A
S269A
K272A
D273A
E275A
E276A
E282A
N""
Cl)
IC)
W > I)
Z, Z
tl'
Q283A
D286A
C
rN
Figure 2.5 Alanine-scanning mutagenesis of EnvZ.
(A) Sequence of the DHp domain of EnvZ showing the residues substituted with alanine in purple.
The conserved histidine phosphorylation site is shaded in grey. Numbering and secondary
structure elements indicated as in Figure 2.2C. (B) Autophosphorylation levels of each EnvZ
alanine mutant after a 1 minute incubation, expressed as a percentage of that measured for wildtype EnvZ. For gel images, see Figure 2.6A. (C) Decrease in EnvZ-P band after incubation with
OmpR. Each value was expressed as a percentage of the decrease measured for wild-type
EnvZ. Mutants that do not show a decrease in EnvZ-P could be defective either in
phosphotransfer or in dephosphorylation of OmpR-P (see text for details). (D) Phosphatase
activity of EnvZ alanine mutants. Each alanine mutant was tested for dephosphorylation of
OmpR-P and the rate expressed as a percentage of that measured for wild-type EnvZ. (E)
Phosphotransfer from EnvZ alanine mutants to RstA. Phosphotransfer was assessed by
measuring the increase in labeled RstA after a 10 second incubation. For each mutant, the
increase in RstA was normalized to the autophosphorylation level for that kinase and then
reported as a fold-change relative to the phosphotransfer for wild-type EnvZ to RstA. In panels BE, the specificity residues are listed in orange, as in Figure 2.2C. For panels C and E, the mutant
kinases were autophosphorylated for 60 minutes prior to assessing phosphotransfer. Mutants
D244A and L249A did not autophosphorylate significantly enough to examine phosphotransfer.
For gel images for panels C-D, see Figure 2.6B. For panel D, the mutant kinases were tested for
dephosphorylation of OmpR-P at 0.5, 1, and 2 minutes (Figure 2.7).
or the
highly
conserved
aspartate
that
follows,
D244,
completely
abolished
autophosphorylation. Other residues strongly affecting autophosphorylation flank H243,
including L236, G240, R246, T247, P248, L249, R251, and 1252. Many of these residues
are highly conserved among all histidine kinases suggesting they are critical for
catalyzing phosphoryl transfer from ATP to histidine. Alternatively, they may impact
folding or stability of the kinase; however, these residues are mostly solvent-exposed and
none of the mutants significantly affected purification of soluble protein (data not
shown). Of the top coevolving residues (Figure 2.2), only R25 IA showed substantially
lower autophosphorylation than wild type, suggesting that residues required for docking
to a response regulator are distinct from those required for docking to the kinase's CA
(catalytic ATP-binding) domain.
For each EnvZ mutant that was able to autophosphorylate to reasonably high levels after
an extended incubation, we tested phosphotransfer to OmpR, CpxR, and RstA (Figure 2.5
Capra 172
C-E, 2.6A). For an assessment of significance, see Figure 2.6C and Materials and
Methods. For wild-type EnvZ, phosphotransfer to OmpR manifests as a decrease in the
EnvZ-P band and a weak or absent OmpR-P band, resulting from high rates of
phosphotransfer and subsequent dephosphorylation of OmpR~P by EnvZ.
Several
alanine mutants did not show the same decrease in EnvZ-P as the wild-type protein.
However, for most of these mutants, such as R246A, T247A, and P248A, a more intense
OmpR~P band was also seen, suggesting that phosphotransfer had occurred but that the
mutant could no longer dephosphorylate OmpR-P.
We confirmed the loss of
phosphatase activity by measuring the dephosphorylation of purified OmpR-P by each
EnvZ mutant (Figure 2.5D, 2.7). Only one mutant, 1252A, showed a significant defect in
phosphotransfer with no effect on phosphatase activity. Strikingly, mutating most of the
coevolving specificity residues, including T250, R251, A255, E257, M258, S269, K272,
and D273 had no major effect on phosphotransfer to OmpR. This finding suggests that
there is no single "hot spot" and, instead, that specificity and molecular recognition are
distributed over a number of residues. There may also be non-additive or synergistic
effects between residues such that single point mutations do not significantly affect
phosphotransfer in isolation, a possibility probed in more detail below.
Finally, we examined the EnvZ alanine mutants for phosphotransfer to the non-cognate
regulators RstA and CpxR (Figure 2.5D, 2.6B). For these reactions, in contrast to those
shown in Figure 2, EnvZ constructs were autophosphorylated
and tested for
phosphotransfer without purifying them away from ATP. Under these conditions, EnvZ
phosphotransfers weakly to RstA, permitting us to assess whether the alanine mutations
affected this non-cognate interaction. Most mutants phosphorylated RstA at a level
Capra 173
A
cc @
B
L230A
R234A
T235A
T250A
R251A
1252A
L236A
G240A
R24A
T247A
X
0N
N
a
8
N10
z
P248A
HK 1
RR
b
Ill.
R253A
L254A
I
Ill I1
E261A
A255T
T256A
E257A
Ill Ill . i
HKW
RR
M258A
M259A
S260A
K272A
D273A
E275A
Q262A
D263A
G264A
S269A
HK I
RRW
E276A
E282A
Q283A
D286A
WT
IL
HK P
RRW
C
120
100
) so
60
U
:11 i i
transfer to OrnpR
(decrease
In EnvZ-P)
__
transfer to RtA
(increase In RMtA-P)
Figure 2.6 Alanine scanning mutagenesis of EnvZ.
(A) Each EnvZ mutant was autophosphorylated for 1 minute before reactions were stopped by
the addition of loading buffer. Kinases were then examined by SDS-PAGE and phosphorimaging
using four separate protein gels that were handled identically. Scanned images were
concatenated; vertical bars separate lanes from different gels. For quantification see Figure 2.5B.
(B) Each EnvZ mutant was autophosphorylated for 60 minutes and then examined for
phosphotransfer to OmpR, RstA, and CpxR. Phosphotransfer was assessed by measuring the
decrease in labeled EnvZ after a 10 second incubation with OmpR. For quantification, see Figure
2.5 C and E. (C) Reproducibility of phosphotransfer assays. Wild-type EnvZ was examined for
phosphotransfer to OmpR and RstA six times while mutants T247A, L254A, and E257A were
examined three times. The graph shows the mean and the individual values in red.
Capra 174
U
(min.)
0
WT
-
0.C
1
2
G.A
1
L230A
R234A T235A
G240A
0. 1 2 0.5 1 2 0.5 1 2 0.5 1 2
2
OmpR-P
1
2
L254A
0.5 1 2
A256T
0.A 1 2
E257A
0.
1
2
R251A M258A
0.5 1 2 0.1 1 2
S269A
0. 1 2
D273A
0.
1
2
i
-
.me(min.)
T250A
CA
0
WT
-
0.5
1
2
0.5
2
0.C
1
2
L236A R246A
0.5 1 2 0.5 1 2
2
0.
T247A
0.5 1 2
P248A
0.6 1 2
1252A
0.5
R253A
2
0
K272A
0. 1 2
0.
1
1
2
T256A
0.
1
2
M259A
S260A
0.5 1 2 0.5 1 2
OmpR-P
Om (min.)
OmpR-P
-
-
0 0.
1
WT
1
E261A
1
2
Q262A
0.
1
2
D263A
0.5
1
2
G264A
0.
1
2
E275A
1
2
E276A
0.
1
2
E282A
0. 1 2
Q283A
0. 1 2
D286A
0.5 1 2
_
Figure 2.7 Dephosphorylation of OmpR-P by EnvZ alanine mutants.
Phosphorylated OmpR was purified and incubated with each EnvZ mutant for 0.5, 1, and 2
minutes. For a quantification of rates relative to wild-type EnvZ see Figure 2.5D.
equivalent to or less than the wild type EnvZ. However, four mutants, P248A, A255T,
E257A, and D273A, each showed increases in RstA phosphorylation; E257A also
showed detectable phosphorylation of CpxR. Notably, three of the four residues were
identified as specificity residues (Figure 2.2) in our coevolution analysis. The increase in
cross-talk seen with these mutants suggests that these residues function, at least in part, as
negative elements that prevent phosphotransfer to non-cognate substrates without
significantly affecting transfer to the cognate substrate.
Capra 175
Characterization of all intermediates along the mutational trajectories
separating EnvZ and RstB
Although alanine-scanning provides some insight into specificity, an alanine substitution
does not necessarily result in a simple loss of functionality, especially considering that
EnvZ has a specificity residue that is already an alanine. In addition, as noted, there may
be non-additive interdependencies between residues such that individual substitutions
have minimal effect.
We therefore sought to characterize the role of specificity-
determining residues by examining the complete set of mutational intermediates between
two histidine kinases with different specificities. For this analysis we focused on the
paralogous systems EnvZ/OmpR and RstB/RstA, and term the approach trajectoryscanning. We constructed each possible specificity intermediate between EnvZ and RstB.
This was feasible as the conversion of EnvZ phosphotransfer specificity to match that of
RstB required only three substitutions, T250V, L254Y, and A255R (Skerker et al., 2008);
the other major specificity residues identified by coevolution analysis are identical
between EnvZ and RstB. In addition, we were able to rewire the specificity of RstB to
match that of EnvZ by mutating the same three sites (Figure 2.8).
The triple mutant
RstB(V228T, Y232L, and R233A) no longer phosphorylated RstA and, instead,
efficiently phosphorylated OmpR. These three residues thus play the dominant roles in
dictating the specificity of both EnvZ and RstB.
Other residues may make minor
contributions.
We constructed each possible single and double mutant intermediate between EnvZ and
RstB, in the context of each protein for a total of 12 mutants. To simplify nomenclature
we have named mutants based on the protein mutated and the identity of the three
Capra 176
A
VLA
VYA
TYA
VLR
HK 0
RR0,
EnvZ(TLA)
X
VYR
RstB
cc~
H
HK 10
RRO t
TLR
TYR
E E
HK D
RR b'
VLA
B
VYA
HK I
CL
RR 1
EnvZ(TLA)
TLA
M
TYA
VLR
TLR
TYR
CL
RstB(VYR)
HK W
RR No
E,
HK 0
RR
b
Figure 2.8 Converting the phosphotransfer specificity of EnvZ to match RstB and
vice versa.
(A) Converting the phosphotransfer specificity of EnvZ to that of RstB. Wild-type EnvZ and each
single, double, and triple mutant on the trajectory from EnvZ to RstB were autophosphorylated
and then incubated alone or with one of three response regulators, as indicated, for 10 seconds.
(B) Converting the
Wild-type RstB (far right) is shown for comparison to EnvZ(VYR).
phosphotransfer specificity of RstB to that of EnvZ. Wild-type RstB and each single, double, and
triple mutant on the trajectory from RstB to EnvZ was autophosphorylated and then incubated
alone or with one of three response regulators, as indicated, for 60 seconds. Wild-type EnvZ (far
left) is shown for comparison to RstB(TLA). Arrows connect profiles of mutants differing by a
Capra 177
single amino acid substitution.
specificity residues being considered. For example, wild-type EnvZ is EnvZ(TLA) and
the single point mutant EnvZ(T250V) is EnvZ(VLA).
Each mutant was tested for
phosphotransfer to the regulators OmpR, RstA, and CpxR (Figure 2.8).
Under the
conditions used, the wild type EnvZ and RstB are specific for, and only phosphorylate,
their cognate substrates, OmpR and RstA, respectively.
In the context of EnvZ, each single mutant continued to phosphorylate OmpR (Figure
2.8A).
The
single
mutants
EnvZ(TYA)
and
EnvZ(TLR)
also
showed
weak
phosphorylation of RstA. Of the double mutants, EnvZ(VYA) and EnvZ(TYR) both
preferentially phosphorylated RstA, with the former not detectably phosphorylating
OmpR and the latter only weakly phosphorylating OmpR. The other double mutant,
EnvZ(VLR) appeared to have an approximately equal preference for phosphotransfer to
RstA and OmpR. In the context of RstB, none of the three single mutants had a major
effect on specificity and each continued to phosphotransfer only to RstA (Figure 2.8B).
By contrast, the double mutants each behaved differently; the mutant RstB(TYA)
phosphorylated only RstA, the mutant RstB(TLR) was promiscuous and phosphorylated
RstA, OmpR, and CpxR, while the mutant RstB(VLA) did not phosphorylate any of the
response regulators under these reaction conditions.
The systematic mapping of the mutational trajectories from EnvZ to RstB and vice versa
led to several interesting observations (Figure 2.8). First, the behaviors of intermediates
along individual trajectories are often quite different. The most dramatic example is the
double mutants of RstB, with RstB(TLR) phosphorylating all three substrates examined,
Capra 178
RstB(TYA) phosphorylating only RstA, and RstB(VLA) not phosphorylating any of the
substrates. Second, we found that the individual specificity residues strongly influence
each other. For example, the substitution V228T in the wild type RstB had very little
effect on substrate preference, while the same substitution into RstB(VLA) converted a
kinase that phosphorylated none of the regulators into a kinase that specifically
phosphorylates OmpR (Figure 2.8B). The effect of the V228T substitution thus depends
critically on the identity of other residues. As another example, the substitution Y230L in
wild type RstA had little effect on specificity, but when introduced into RstA already
harboring the V228T substitution produced a kinase that phosphorylated OmpR, RstA,
and CpxR (Figure 2.8B). Similar observations were made for each of the other residues.
Collectively, these data indicate that each specificity residue does not contribute
independently or additively to the overall substrate specificity of a kinase. Rather, their
contributions are frequently epistatic to one another and display context-dependence.
A complete specificity map of the mutational trajectories separating
EnvZ/OmpR and RstB/RstA
The mutational trajectory scanning done for both EnvZ and RstB was extended to the
response regulator OmpR. Converting OmpR to have the phosphotransfer specificity of
RstA required 3 mutations in alpha helix-I and 3 mutations in the 135-C5 loop (Figure
2.4A).
We treated the loop as a single entity and made the 15 possible OmpR-RstA
intermediates: 4 single, 6 double, 4 triple, and 1 quadruple mutant. We then examined
phosphotransfer from each of the 7 EnvZ-RstB mutants (Figure 2.8A), as well as wild
type EnvZ, RstB, and CpxA, to each of the 15 OmpR mutants and to wild-type OmpR,
RstA, and CpxR, for a total of 180 pairwise combinations. The complete data are shown
Capra 179
OmpR mutants
E
0
z. Z z Z M Z z M z M M z M M M M
r rZOZZOZO.A
HKW
EnvZ (TLA)
RR Do
*VLA
HKA
VYA
RR Il
HK
TYR
RR10
HK
RR No
RR
HK No
'
VA
TR
HK
RR No
HK
RR Do
CpYA
TY
11
HK
RR ll
HKW
od
.
CpxA
RR 10
HK
RR 0-
Capra 180
Figure 2.9 Complete trajectory-scanning mutagenesis of EnvZ and OmpR.
Each histidine kinase, indicated on the far right, was autophosphorylated and tested for
phosphotransfer to each of the response regulators listed across the top. Mutants of EnvZ are
named according to the identity of the three specificity residues being examined; for instance,
wild-type EnvZ is 'TLA' whereas the mutant T250V is 'VLA'. Mutants of OmpR are named
similarly. All phosphotransfer reactions were incubated for 10 seconds with the exception of RstB
and CpxA, which were examined at both 10 seconds and 1 minute. Each kinase profile was
composed of two separate gels that were run, exposed to phosphor screens, and scanned in
parallel. The resulting two gel images were treated identically and then stitched together between
OmpR(EVAPFN) and OmpR(EVATTP).
in Figures 2.9 and 2.10. All phosphotransfer reactions were run for 10 seconds, except
for RstB and CpxA, which were run for 10 seconds and for 1 minute. To evaluate
phosphotransfer, we quantified the relative intensity of each response regulator band for a
given histidine kinase, yielding a profile of phosphotransfer activity for each kinase.
From the comprehensive profiles, several observations and trends emerged (Figure 2.9,
2.10).
First, the triple mutant EnvZ(VYR) robustly phosphorylated wild type RstA as well as
the quadruple mutant of OmpR in which all major specificity residues have been mutated
to match those found in RstA. EnvZ(VYR) no longer phosphorylated OmpR, consistent
with a complete change in specificity. However, it still phosphorylated two other OmpR
mutational intermediates that the wild type RstB kinase did not, at least at the time point
examined.
This comparison supports the notion that the three residues we mutated in
EnvZ are the dominant determinants of partner specificity, but that other residues play
minor, fine-tuning roles, particularly in preventing non-cognate interactions.
Second, the data demonstrated that EnvZ and OmpR can tolerate some mutations in the
specificity residues of their partner and still retain the ability to readily phosphotransfer.
Wild-type EnvZ phosphorylated each of the single mutants of OmpR and three of the six
Capra 181
B
TJIR:
DL
C
TLA
VIA
TYA
VLR
A
E
BVYA
F
TYR
VYR
RstB
RstB
[CpxA
LCpxAA
Figure 2.10 Hierarchical clustering of trajectory-scanning mutagenesis of EnvZ
and OmpR.
Phosphotransfer profiles for each EnvZ construct examined in Figure 5 were quantified. The
intensity of each response regulator band within a given kinase profile was expressed as a
percentage of the maximally phosphorylated response regulator in that profile. Profiles were then
clustered in two-dimensions, with the resulting tree shown for the response regulators (top) and
histidine kinases (left). For each tree, the major clusters of EnvZ and OmpR mutants are
designated by letters. The 1 minute time point profiles for RstB and CpxA are indicated by '^'.
double mutants nearly as well as it phosphorylated wild-type OmpR; however, it did not
significantly phosphorylate the triple mutants or the quadruple mutant. Wild-type OmpR
was efficiently phosphorylated by each of the EnvZ single mutants and one of the double
mutants, but not by the triple mutant.
Third, these profiles reveal mutational paths from the specificity of the EnvZ/OmpR pair
to that of RstB/RstA in which phosphotransfer is maintained. In other words, there is an
Capra 182
ordered series of single mutations that can be made in EnvZ and OmpR that convert them
to the specificity of RstB and RstA, respectively, without disrupting their ability to
phosphotransfer to one another along the way.
For example, wild-type EnvZ
phosphorylates OmpR and the single mutant OmpR(RLAPFN) to similar levels, and
conversely
the
single
mutant
EnvZ(TLA)
phosphorylates
both
OmpR
and
OmpR(RLAPFN). In Figure 2.11 we extend this example to show how EnvZ and OmpR
could, in principle, change its specificity to that of the RstB/RstA system by a series of
alternating mutations in the two molecules without ever severely disrupting their
interaction. There are several such paths, although each path is not necessarily equivalent
because CpxA phosphorylates some mutational intermediates of OmpR and some EnvZ
mutants phosphorylate CpxR.
For instance, EnvZ(TLR) phosphorylated CpxR, and
OmpR(ELRPFN) was phosphorylated by CpxA (Figure 2.9, also see Figure 2.8). The
avoidance of cross-talk may limit the possible evolutionary pathways between
EnvZ/OmpR and RstA/RstB, or at least favor some relative to others (Figure 2.11).
We also quantified the phosphotransfer profiles for each EnvZ mutant and the wild type
kinases (Figure 2.9) and performed hierarchical clustering in two dimensions, i.e. both
the kinase and regulator dimensions (Figure 2.10). As expected, clustering the kinases
places RstB close to the EnvZ(VYR) while CpxA is separated from EnvZ, the EnvZ
mutants, and RstB.
Similarly, clustering the regulators placed RstA close to the
quadruple mutant OmpR(EVATTP) while CpxR formed a clear outgroup on its own.
The hierarchical clustering analysis provides insight into the relative importance of
individual specificity residues. The profiles were clustered based on phosphorylation
levels, but show a clear correspondence to sequence features.
For instance, the two
Capra 183
primary clusters of OmpR mutants (labeled A and B in Figure 10) differ in the identity of
their P5-a5 loops; that is, each OmpR mutant in cluster A has the residues 'PFN' whereas
each mutant in cluster B has the residues 'TTP'. The branch lengths separating these
clusters are long relative to the total length of the tree, indicating that the identity of the
loop strongly splits the phosphotransfer profiles of the regulators. Within. both cluster A
and B, the next split in the tree correlates with the identity of position 1; that is, each
OmpR mutant in cluster C (or cluster E) has an arginine at position 1 while each OmpR
mutant in cluster D (or cluster F) has a glutamate at position 1. Again, the branch lengths
are relatively long indicating a clear correlation between phosphotransfer behavior and
sequence. The next split is based on identity at the second position, either a leucine or
valine. The final split is based on the identity at the third position. In each case, this final
split has extremely short branch lengths, reflecting the near identity of each profile pair
that follows the split. In sum, the clustering analysis suggests a hierarchy to the
contribution made by individual specificity residues within the regulators. The loop,
which includes three residues, made the strongest contribution, followed by, in order,
positions 1 > 2 > 3. A similar analysis was applied to the EnvZ mutants revealing that
position 2 (Y or L) drives the initial clustering of EnvZ mutants, followed by position 3
(R or A), and finally position I (V or T).
Capra 184
Discussion
Determinants of specificity in paralogous protein families
Maintaining specificity and preventing unwanted cross-talk between highly similar
proteins is a fundamental challenge for cells, and one that remains poorly understood. In
many cases molecular recognition plays a critical role, but the ability to pinpoint the
amino acids responsible and to determine the contributions of each residue to specificity
has been elusive.
Here, we tackled this problem in the context of bacterial two-
component signal transduction systems where specificity is dictated by molecular
recognition (Skerker et al., 2005). We note, however, that two-component signaling
pathways are not insulated at all levels - for instance, distinct signaling pathways
sometimes converge transcriptionally by regulating overlapping sets of genes (Laub and
Goulian, 2007).
However, the focus here is on the specificity of phosphotransfer for
which there is little evidence of significant, physiologically-relevant cross-talk (Laub and
Goulian, 2007).
To identify the amino acids that enforce the specificity of phosphotransfer, we examined
patterns of amino acid coevolution in cognate kinase-regulator pairs.
However,
computational approaches alone do not unequivocally establish which residues are
critical for specificity or reveal how each contributes to substrate selection. We therefore
focused on experimentally rewiring the specificity of the model two-component proteins,
EnvZ and OmpR. Previously we reported that EnvZ could be rewired to exhibit the
substrate specificity of RstB by mutating as few as three of the coevolving residues
(Skerker et al., 2008). Here we extended these results by rewiring OmpR to partner
specifically with the histidine kinase RstB instead of EnvZ.
Capra 185
The residues mutated to rewire the partnering specificity of EnvZ and OmpR are
predicted to be in close physical proximity during phosphotransfer. While no structure of
EnvZ bound to OmpR exists, a co-crystal structure of a histidine kinase from Thermotoga
maritima in complex with its cognate response regulator was recently solved (Casino et
al., 2009) and can be used to infer physically proximal residues for EnvZ and OmpR.
However, the spatial proximity of residues does not reveal how they govern specificity
and whether individual residues promote the binding of a cognate protein or prevent
interactions with non-cognate proteins. Moreover, the relative contribution made by each
residue is difficult to discern from structural or spatial considerations alone.
To better dissect the role played by individual residues, we used alanine-scanning
mutagenesis of EnvZ. However, of the nine major specificity residues in EnvZ (Figure
2.2), only one disrupted phosphotransfer to OmpR when mutated to alanine. These data
suggest that no major hot spot exists for the EnvZ-OmpR interaction and that specificity
is distributed across the interface. However, single alanine mutants do not always reveal
the role of a particular residue. For example, EnvZ(L254A) showed very little change in
substrate specificity, whereas EnvZ(L254Y) (Figure 2.8A) showed a significant level of
cross-talk
to RstA.
Alanine-scanning
mutagenesis
also
ignores
any
potential
interdependencies that may exist between residues. Such relationships and non-additive
effects on specificity were revealed in our comprehensive characterization of the
mutational intermediates separating EnvZ and RstB. In several cases, the effect of a
given substitution on phosphotransfer specificity depended significantly on what other
substitutions had already been made; for example the mutation A255R in EnvZ had very
little effect in the context of EnvZ(VYA) but led to significant promiscuity in the context
Capra 186
of EnvZ(TLA). These sorts of contextual and epistatic effects have been seen in other
studies of molecular interaction specificity including corticosteroid receptor-ligand
interaction (Ortlund et al., 2007) and transcription factor-DNA binding (Carlson et al.,
2010).
In principle, the context dependence of amino acids could lead to 'negative'
epistasis in which one mutation on its own is detrimental until a second mutation is
introduced. For example, the protein P-lactamase has evolved resistance to cefotaxime
by accumulating five different mutations (Weinreich et al., 2006). While each mutation
contributes to resistance, certain mutations actually decrease resistance unless, or until,
one of the other mutations also occurs. We did not see any obvious case of negative
epistasis when converting EnvZ to RstB or converting OmpR to RstA, as each mutation
either increased interaction with the target molecule or had no effect. However, negative
epistasis could exist when converting the specificity of other two-component signaling
proteins.
Evolutionary implications
Our trajectory-scanning analysis provides a glimpse into the possible evolutionary history
of two-component signaling proteins.
The EnvZ/OmpR and RstB/RstA systems are
relatively closely related and likely evolved by duplication of a common progenitor
followed by sequence divergence, including at specificity sites. Mutations in specificity
residues following duplication presumably required corresponding changes in their
cognate regulators in order to maintain operation of each pathway as they diverged from
one another to avoid pathway cross-talk. Our results demonstrate that an ordered series
of mutations could occur in EnvZ and OmpR such that the two proteins would maintain
significant levels of phosphotransfer while transiting through sequence space to the
Capra 187
A
B
EnvZ
OmpR
TLA
TLA
TYA
TYA
TYR
RLR I PFN
RLR / TTP
RLR I TTP
RLA I TTP
RLA I TTP
ELA / TTP
ELA / TTP
EVA / TTP
TYR
VYR
VYR
OmpR mutants
OmpR
single
double
quadruple
(RatA)
'Iiawl
ELRIPF1
EnvZ
triple
TLA
EVRITTP
ELR/TTP
EVArTP
ELArTP
:AN",
------------ELR/PFN
TYA
RLRIPFN RLAIPFN
RLR/TTPRVRIPFN
ELR/PFN
RLAIPFN
EnvZ
mutants
TYR
EVRIPFN
ELAIPFN
RVA/PFN
EVAIPFN
RVATTPI
EVR/TTP/
ELAITTP
EVAIPFN
RVAITTP
RLRIPFN -%RLRITTP n~rrTPKA/TTPE
- IRLAflrFP \ EVRfrIP/
RVRIPFN
VYR
EVRIPFN
ELA/PFN
RVA/PFN
RLAlTTP\
ELR[TTP
RVRkTTP
RLRIPFN
ELRITTP
RVRITTP
ELR/PFN
EVRIPFN
ELAIPFN
EVAIPFN
RLAIPFN
RVAIPFN
RVA/TTP
aRfLTP-
RVRIPFN
VAir
V, tP
ELAITTP
RLAfTP\ EVRTTP/
ELRrrTP
ELATTP
RVRITTP
merge
Figure 2.11 Mutational trajectories from EnvZ/OmpR to RstB/RstA.
EnvZ and OmpR can be converted by a series of single mutations to harbor the specificity
residues found in RstB and RstA, respectively, without disrupting phosphotransfer in intermediate
stages. (A) A series of single mutations can convert the specificity of EnvZ to match that of RstB
and OmpR to match RstA. Starting with the wild type specificity residues in red text at the top,
each subsequent line introduces a single mutation (shown in black text) until both sets of
specificity residues have been completely changed. As noted in the text, we treated the loop as a
single mutation. As shown in panel B, each kinase-regulator pair listed is capable of
phosphotransfer and does not include a regulator that is phosphorylated by CpxA. (B) The
complete set of intermediates between wild type OmpR (RLR/PFN) and the quadruple mutant
(EVA/TTP) are listed. For wild type EnvZ (TLA), the single mutant EnvZ(TYA), the double mutant
EnvZ(TYR), and the triple mutant EnvZ(VYR), the set of OmpR mutants recognized by each
kinase are shaded, with a merge of all four at the bottom. Mutants that are phosphorylated by
CpxA are listed in grey text, all others in black text. Bold lines connect the mutant series shown in
panel A.
Capra 188
specificity residues of RstB/RstA (Figure 2.11), or vice versa. In addition, this series of
mutations can occur without ever entering the sequence space occupied by another
closely
related
(in
sequence)
pair, CpxA/CpxR thereby
preventing
cross-talk.
Interestingly though, not all mutational trajectories have these characteristics of
maintaining phosphotransfer and avoiding cross-talk, raising the possibility that sequence
evolution following duplication is constrained or that natural selection may have favored
certain trajectories over others.
lambdoid
phage
integrases,
Analysis of other proteins, including P-lactamase,
hormone
receptors,
and
the
metabolic
enzyme
isopropylmalate dehydrogenase (Bridgham et al., 2009; Dorgai et al., 1995; Lunzer et al.,
2005; Weinreich et al., 2006), have led to similar suggestions about the constraints on
protein evolution.
Our trajectory scanning approach is related to other systematic studies of protein-protein
interaction specificity, including homolog-scanning (Cunningham et al., 1989) and sitesaturation mutagenesis (Miyazaki and Arnold, 1999).
In many cases, however, such
approaches involve single substitutions rather than an exploration of the entire mutational
landscape separating two different proteins. Because the major specificity-determining
residues of two-component signaling proteins have been previously mapped and are
relatively limited in number, we were able to systematically generate all intermediates
between EnvZ/OmpR and RstB/RstA.
We note, however, that for the three major
specificity residues in EnvZ, T250, L254, and A255, conversion to the corresponding
residue in RstB requires two nucleotide substitutions. There are thus a great number of
additional mutational intermediates that will be important to characterize in the future
when considering the evolutionary history of EnvZ and RstB.
Capra 189
Intriguingly, our clustering analysis of the trajectory-scanning data also reveals an
underlying hierarchy of the specificity-determining residues in EnvZ and OmpR. The
clusters mapped based on phosphotransfer relationships were strongly correlated with the
sequence of specificity residues.
For example, the first branch point in the histidine
kinase clusters separated those with a leucine at position 254 in EnvZ from those with a
tyrosine at that position.
These observations demonstrate that different residues
contribute unequally to specificity. So although our alanine-scanning mutagenesis did
not reveal any major hot spots and suggested that specificity is distributed, the trajectoryscanning study indicates that certain residues play more important roles than others. It
will be interesting to see whether the hierarchies revealed here have influenced or
constrained evolutionary trajectories of two-component signaling proteins, and if the
relative importance of positions is similar in other two-component pairs.
Rational rewiring of two-component signaling pathways
The rational rewiring of two-component signaling proteins represents a stringent test of
how well specificity is understood.
Additionally, it opens the door to improved
construction of synthetic signaling pathways in bacteria. Here, we used analyses of amino
acid coevolution to guide the rational rewiring of -the response regulator OmpR, a
prototypical DNA-binding response regulator. With only a handful of mutations, the
phosphotransfer specificity of OmpR was rewired to match that of RstA or CpxR. A
recent study of Rhodobacter used structural data to guide the rewiring of chemotaxis
response regulators to partner with the non-cognate kinase CheA 3 (Bell et al., 2010). The
residues mutated in that study were in alpha helix I of the response regulator and most
were identified here as coevolving residues. A genetic screen for altered partnering
Capra 190
specificity of the regulator PhoB also identified residues in alpha helix 1 (Haldimann et
al., 1996). The successful rewiring of CheY and PhoB along with EnvZ and OmpR
suggests that two-component proteins will be generally amenable to synthetic biology.
However, it is not yet clear whether any histidine kinase (or response regulator) can be
reprogrammed to behave like any other histidine kinase (or response regulator). For
example, response regulators have been categorized into eight subfamilies, with the
majority falling into just three (Grebe and Stock, 1999). OmpR, RstA, and CpxR all fall
within one subfamily perhaps facilitating the interconversion of their specificities.
Another important challenge for the future is to create novel kinase-regulator pairs with
specificity residues that are orthogonal to those used in naturally occurring pairs. The
functional hierarchies and interdependencies identified here will be important guides in
engineering new, specific interactions. Similarly, these functional relationships should
help in designing better algorithms for predicting kinase-regulator pairs in genomes of
interest.
Final perspective
The life of a cell depends critically on the specificity of protein-protein interactions. Yet
we still have a relatively primitive understanding of how such specificity is encoded
within proteins and how a set of amino acids can allow binding of a cognate partner while
excluding all other non-cognate partners. Two-component signal transduction systems
represent an ideal model for addressing these fundamental issues as specificity is
determined predominantly by a small set of residues. The consequent reduction in scope
and scale enabled the systematic and comprehensive analyses presented here.
More
generally, the approaches used, including analyses of amino acid coevolution and
Capra I 91
trajectory-scanning mutagenesis, will be widely applicable to the study of specificity and
molecular recognition in many other protein-protein interactions.
Capra 192
Materials and Methods
Sequence analysis
The software HMMER (http://hmmer.org) was used, with an E-value cutoff of 0.01, to
identify and align histidine kinase and response regulator sequences from fully sequenced
bacterial genomes in GenBank. For histidine kinases, the models HisKA, HisKA_2,
HisKA_3, and HWE_HK from the PFAM database were used. For response regulators,
the model Response reg was used. Histidine kinases and response regulators with
GenBank genome identifier numbers differing by one, indicating adjacent genes, were
identified, concatenated, and treated as cognate pairs. Sequences were filtered to ensure
that no two sequences were more than 90% identical.
The final set contained 4375
concatenated pairs of histidine kinase and response regulators. Columns in the multiple
sequence alignment (MSA) containing greater than 10% gaps were eliminated.
Mutual information (MI) between columns was measured as described previously
(Skerker et al., 2008). MI scores were adjusted to account for differences in the average
MI of each column. For columns i and j in a multiple sequence alignment, we defined
2
MI(,j)aj = MI(i,j)raw / (MI(i)avg + MI(j)avg)/ where MI(i)avg and MI(j)avg
are the average
MI scores for column i and j paired with every other column in the alignment.
Clustering
Phosphorylation profiles in Figure 2.10 were constructed by quantifying response
regulator bands in each profile (Figure 2.9) using ImageQuant (GE Healthcare) and then
normalizing such that each regulator's value was represented as a percentage of the
maximally phosphorylated regulator for a given kinase. Profiles were then subjected to
Capra 193
hierarchical clustering in two dimensions, with response regulators clustered using
uncentered correlation and histidine kinases using Euclidean distance.
Profiles were
clustered using Cluster 3.0 (de Hoon et al., 2004) and visualized using Java Treeview
(Saldanha, 2004).
Protein purification
All cloning and site-directed mutagenesis was done with Gateway pENTR vectors
(Invitrogen)
following
procedures described previously
(Skerker et al., 2008).
Mutagenesis primers are listed in Table 2.1. Clones in pENTR vectors were mobilized
into destination vectors for expression and purification using Gateway LR reactions
according to the manufacturer's protocol (Invitrogen). Histidine kinases were moved into
pDEST-His 6 -MBP and response regulators into pDEST-TRX-His 6 .
Expression and
purification was carried out exactly as described previously (Skerker et al., 2005).
Table 2.1 -
Primers
Primer Name
Sequence*
OmpR(R1 5E)
OmpR(L16V)
OmpR(R22A)
OmpR(R15E;L16V)
OmpR(R22E;Y23L)
OmpR(P1 06T,F1 07T,N 1 08P)
OmpR(P109D)
EnvZ(T250V)
RstB(V229T)
RstB(Y233L)
RstB(R234A)
RstB(Y233L;R234A)
RstB(Y233L)_onV229T
RstB(V229T;Y233L)_onR234A
EnvZ(L230A)
EnvZ(R234A)
EnvZ(T235A)
GTCGATGACGACATGGAGCTGCGTGCGCTGCTG
GACGACATGCGCGTGCGTGCGCTGCTG
GCGCTGCTGGAAGCTTATCTCACCGAA
GATGACGACATGGAGGTGCGTGCGCTGCTG
CGTGCGCTGCTGGAAGAACTGCTCACCGAACAAGGC
GACTACATTCCAAAAACGACGCCGCCGCGTGAACTGCTG
AAACCGTTTAACGACCGTGAACTGCTG
ACGCCGCTGGTGCGTATTCGC
CGAACACCGTTAACGCGCCTGCGTTAT
GTGCGCCTGCGTCCTCGACTGGAGATG
CGCCTGCGTTATGCACTGGAGATGAGC
TTAGTGCGCCTGCGTCTTGCACTGGAGATGAGCGAT
ACGCGCCTGCGTCTTCGACTGGAGATG
CGAACACCGTTAACGCGCCTGCGTCTT
GGTGTTAAGCAAGCGGCGGATGACCGC
CTGGCGGATGACGCCACGCTGCTGATG
TGGCGGATGACCGCGCGCTGCTGATGGCGGG
Capra 194
EnvZ(L236A)
EnvZ(G240A)
EnvZ(D244A)
EnvZ(R246A)
EnvZ(T247A)
EnvZ(P248A)
EnvZ(L249A)
EnvZ(T250A)
EnvZ(R251A)
EnvZ(1252A)
EnvZ(R253A)
EnvZ(L254A)
EnvZ(A255T)
EnvZ(T256A)
EnvZ(E257A)
EnvZ(M258A)
EnvZ(M259A)
EnvZ(S260A)
EnvZ(E261A)
EnvZ(Q262A)
EnvZ(D263A)
EnvZ(G264A)
EnvZ(S269A)
EnvZ(K272A)
EnvZ(D273A)
EnvZ(E275A)
EnvZ(E276A)
EnvZ(E282A)
EnvZ(Q283A)
EnvZ(D286A)
CGGATGACCGCACGGCGCTGATGGCGGGGGT
CGCTGCTGATGGCGGCGGTAAGTCACGACTT
CGGGGGTAAGTCACGCGTTGCGCACGCCGCT
TAAGTCACGACTTGGCGACGCCGCTGACGCG
GTCACGACTTGCGCGCGCCGCTGACGCGTAT
GACTTGCGCACGGCGCTGACGCGTATT
TTGCGCACGCCGGCGACGCGTATTCGC
TGCGCACGCCGCTGGCGCGTATTCGCCTGGC
GCACGCCGCTGACGGCGATTCGCCTGGCGAC
CCGCTGACGCGTGCTCGCCTGGCGACT
CGCTGACGCGTATTGCGCTGGCGACTGAGAT
ACGCGTATTCGCGCGGCGACTGAGATG
CGTATTCGCCTGACGACTGAGATGATG
ATTCGCCTGGCGGCTGAGATGATGAGC
CGCCTGGCGACTGCGATGATGAGCGAG
GCCTGGCGACTGAGGCGATGAGCGAGCAGGA
TGGCGACTGAGATGGCGAGCGAGCAGGATGG
CGACTGAGATGATGGCGGAGCAGGATGGCTA
CTGAGATGATGAGCGCGCAGGATGGCTATCT
AGATGATGAGCGAGGCGGATGGCTATCTGGC
TGATGAGCGAGCAGGCGGGCTATCTGGCAGA
TGAGCGAGCAGGATGCGTATCTGGCAGAATC
TATCTGGCAGAAGCGATCAATAAAGAT
CAGAATCGATCAATGCGGATATCGAAGAGTG
AATCGATCAATAAAGCGATCGAAGAGTGCAA
TCAATAAAGATATCGCGGAGTGCAACGCCAT
ATAAAGATATCGAAGCGTGCAACGCCATCAT
GCAACGCCATCATTGCGCAGTTTATCGACTA
ACGCCATCATTGAGGCGTTTATCGACTACCT
TTGAGCAGTTTATCGCGTACCTGCGCACCGG
*Site-directed mutagenesis was done using the primer listed as well as its reverse complement.
Autophosphorylation and phosphotransfer reactions
For autophosphorylation analysis of alanine mutants, histidine kinases were at a final
concentration of 5 tM in HKEDG buffer (10 mM HEPES-KOH pH 8.0, 50 mM KCl,
10% glycerol, 0.1 mM EDTA, 2 mM DTT) supplemented with 5 mM MgCl2, 500 tM
ATP, and 0.5 tCi [y 32 P]-ATP from a stock at -6000 Ci/mmol (Perkin Elmer). Reactions
were incubated at room temperature for 1 minute, stopped by the addition of 4X loading
Capra 95
buffer (500 mM Tris-HCl pH 6.8, 8% SDS, 40% glycerol, 400 mM P-mercaptoethanol),
and analyzed by SDS-PAGE and phosphorimaging.
For phosphotransfer analysis, histidine kinases were autophosphorylated as above, but
were incubated for 60 minutes at 30'C. Phosphotransfer was assessed by incubating
autophosphorylated kinases with response regulators, each at a final concentration of 2.5
[tM, at room temperature for the indicated time (either 10 seconds or 1 minute).
Reactions were stopped by the addition of loading buffer, and analyzed by SDS-PAGE
and
phosphorimaging.
For
the
experiments
in
Figures
2.4,
2.8
and
2.9,
autophosphorylated kinases were purified away from unincorporated nucleotides by
diluting them 1:10 in HKEDG and then washing eight times in Nanosep 30K Omega
columns (Pall Life Sciences) to minimize the effect of any phosphatase activity. The final
eluate was diluted back to the original volume and MgCl 2 added to 5 mM before
assessing phosphotransfer.
For alanine-scanning mutagenesis, to gauge reproducibility and assess significance in the
changes observed, we repeated the phosphotransfer reactions for wild type EnvZ six
times and a subset of the mutants three times. Standard deviations in each case were -510% of the mean.
Capra 196
Acknowledgements
We thank A. Keating for helpful comments on the manuscript.
Capra 197
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Skerker, J.M., Prasol, M.S., Perchuk, B.S., Biondi, E.G., and Laub, M.T. (2005). Twocomponent signal transduction pathways regulating growth and cell cycle progression in
a bacterium: a system-level analysis. PLoS Biol 3, e334.
Stock, A.M., Robinson, V.L., and Goudreau, P.N. (2000). Two-component signal
transduction. Annu Rev Biochem 69, 183-215.
Ubersax, J.A., and Ferrell, J.E., Jr. (2007). Mechanisms of specificity in protein
phosphorylation. Nat Rev Mol Cell Biol 8, 530-541.
Weigt, M., White, R.A., Szurmant, H., Hoch, J.A., and Hwa, T. (2009). Identification of
direct residue contacts in protein-protein interaction by message passing. Proc Natl Acad
Sci U S A 106, 67-72.
Weinreich, D.M., Delaney, N.F., Depristo, M.A., and Hart, D.L. (2006). Darwinian
evolution can follow only very few mutational paths to fitter proteins. Science 312, 111114.
White, R.A., Szurmant, H., Hoch, J.A., and Hwa, T. (2007). Features of protein-protein
interactions in two-component signaling deduced from genomic libraries. Methods
Enzymol 422, 75-101.
Capra 199
Chapter 3
Adaptive mutations that prevent cross-talk enable the
expansion of paralagous signaling protein families
This work was published as Emily J. Capra, Barrett S. Perchuk, Jeffrey M. Skerker, and Michael
T. Laub. 2012. Cell.
EJC and MTL conceived and designed the experiments. EJC performed all of the experiments.
BSP helped with the protein purifications and the profiles shown in Figure 3.3 JMS contributed
constructs. EJC and MTL wrote the paper.
Capra I 100
Abstract
Orthologous proteins often harbor numerous substitutions, but whether these differences
result from neutral or adaptive processes is usually unclear. To tackle this challenge, we
examined the divergent evolution of a model bacterial signaling pathway comprising the
kinase PhoR and its cognate substrate PhoB. We show that the specificity-determining
residues of these proteins are typically under purifying selection, but have, in Cproteobacteria, undergone a burst of diversification followed by extended stasis. By
reversing mutations that accumulated in an u-proteobacterial PhoR, we demonstrate that
these substitutions were adaptive, enabling PhoR to avoid cross-talk with a paralogous
pathway that arose specifically in u-proteobacteria. Our findings demonstrate that
duplication and the subsequent need to avoid cross-talk strongly influence signaling
protein evolution. These results provide a concrete example of how system-wide
insulation can be achieved post-duplication through a surprisingly limited number of
mutations. Our work may help explain the apparent ease with which paralogous protein
families expanded in all organisms.
Capra 1101
Introduction
The evolutionary forces and selective pressures that influence protein sequences remain
poorly understood at a detailed, molecular level. A comparison of orthologs often reveals
tens to hundreds of amino acid differences. How and why do functionally equivalent
proteins diverge in different organisms? Many of the accumulated substitutions may be
functionally neutral and result from processes such as genetic drift. However, some
mutations may have been adaptive and provided a fitness advantage. Identifying these
beneficial mutations and pinpointing the advantage that they provide are difficult
problems. Comparative sequence analyses, such as measures of codon substitution
patterns or dN/dS ratios (Yang and Bielawski, 2000), can help to identify residues that
are potentially adaptive, but such approaches are frequently insufficient and difficult to
validate. Additionally, elucidating why certain mutations are beneficial requires a
genetically manipulatable organism and an ability to probe the effects of individual
mutations in vivo.
In many cases where protein evolution has been studied experimentally (reviewed in
(Dean and Thornton, 2007)), the relevant proteins were examined in vitro or in
heterologous hosts, and thus outside their native cellular context, possibly eliminating or
obscuring important evolutionary constraints. For example, signal transduction proteins
are often part of large paralogous families that expand through duplication and
divergence. The duplication-divergence process thus runs an inherent risk of introducing
cross-talk with existing pathways. A study of SH3 domains from S. cerevisiae and
humans suggested that the avoidance of cross-talk may represent an important selective
pressure in the evolution of paralogous protein families (Zarrinpar et al., 2003). However,
Capral 102
a direct demonstration that cross-talk influences the evolution of signaling proteins and,
more importantly, an understanding of how this occurs at the amino-acid level are
lacking.
To tackle these challenges we examined the evolution of two-component signal
transduction proteins in bacteria. These pathways, a primary means of signal transduction
in prokaryotes, typically involve a sensor histidine kinase that, upon receipt of an input
stimulus, autophosphorylates and then transfers its phosphoryl group to a cognate
response regulator, which in turn modulates gene expression (Stock et al., 2000). Most
histidine kinases are bifunctional and can, in the absence of an input signal, stimulate the
dephosphorylation
of their cognate
response
regulators,
effectively
acting
as
phosphatases (Huynh and Stewart, 2011).
Although most bacteria encode between 20 and 200 two-component signaling pathways
(Alm et al., 2006), very little cross-talk occurs at the level of phosphotransfer in vivo
(Grimshaw et al., 1998; Laub and Goulian, 2007; Siryaporn and Goulian, 2008; Skerker
et al., 2005). Two-component pathways are highly specific, typically with one-to-one
relationships
between cognate kinases and regulators.
When not stimulated to
autophosphorylate, the phosphatase activity of a given histidine kinase can help to
eliminate cross-talk and the errant phosphorylation of its cognate regulator (Siryapom
and Goulian, 2008). However, when stimulated as a kinase, molecular recognition is the
dominant mechanism for preventing phosphotransfer cross-talk and thereby maintaining
the fidelity of distinct signaling pathways. Systematic analyses of phosphotransfer have
demonstrated that histidine kinases are endowed with an intrinsic ability to discriminate
their in vivo cognate substrate from all other non-cognate substrates (Skerker et al.,
Capra 1103
2005). Analyses of amino acid coevolution in cognate signaling proteins identified the
key specificity-determining residues in histidine kinases and response regulators (Bell et
al., 2010; Capra et al., 2010; Casino et al., 2009; Skerker et al., 2008; Weigt et al., 2009).
Rational mutagenesis of these residues can reprogram the partnering specificity of a
histidine kinase or response regulator (Bell et al., 2010; Capra et al., 2010; Skerker et al.,
2008).
For a given two-component pathway there is likely strong purifying selective pressure on
its key specificity-determining residues to preserve the kinase-substrate interaction. Even
single amino acid changes in specificity residues can drastically change the interaction
capabilities and preferences of a histidine kinase or response regulator (Capra et al.,
2010). Nevertheless, an inspection of orthologous kinases or response regulators often
reveals divergent evolution and variability in the specificity residues of certain subsets of
orthologs, raising the question of whether these changes resulted from neutral or adaptive
processes. We favored the latter, hypothesizing that specificity residues must change in
order to avoid cross-talk between pathways following gene duplication events. Twocomponent signaling pathways often expand through duplication (Alm et al., 2006), and
following such events, bacteria presumably must accumulate mutations that insulate the
new pathways from each other and maintain their isolation from other, existing twocomponent pathways. Here, we provide direct experimental evidence that the avoidance
of cross-talk is indeed a major selective force in the evolution of two-component
signaling pathways. Through in vitro studies and fitness competition assays, we identify
specific substitutions in a model two-component pathway, PhoR-PhoB, that represent an
adaptation to the duplication of another two-component signaling system. Similar
Capral 104
adaptations likely accompanied each of the duplication and divergence events underlying
the massive expansion of two-component signaling protein families in bacteria.
Accordingly, global analyses of specificity-determining residues in extant bacterial
genomes reveal a pervasive trend toward orthogonality in these signaling proteins.
Capra 1105
Results
To identify vertical inheritance of PhoR and PhoB
To examine the divergent evolution of two-component signaling pathways, we focused
on the PhoR-PhoB signaling pathway (Wanner and Chang, 1987), which is found
throughout the bacterial kingdom and helps a wide range of organisms respond to
phosphate starvation. To systematically identify orthologs of E. coli phoR and phoB, we
used a modified version of reciprocal best hits in BLAST analysis that allows for the
identification of putative duplications. Most proteobacteria, except a small number of 8proteobacteria, were found to encode a single ortholog of each phoR and phoB,
suggesting that these genes are rarely duplicated, particularly in the a-, P-, and 7proteobacteria (Figure 3.1A). Additionally, gene trees for phoR and phoB closely
matched a species tree (Figures 3.1B, 3.2A-B), indicating that this signaling system has
likely been vertically inherited in these clades.
Given that phoR and phoB genes were rarely duplicated during the evolution of
proteobacteria, it might be expected that the residues dictating phosphotransfer specificity
would be relatively constant in order to preserve the interaction between PhoR and PhoB.
We thus examined the six residues in PhoR and seven residues in PhoB previously
identified as critical determinants of specificity in two-component signaling proteins
(Capra et al., 2010). We extracted these residues, hereafter referred to simply as
specificity residues, from 149 PhoR orthologs and 92 PhoB orthologs, and built sequence
logos representing the relative frequency of amino acids at each specificity position
(Figure 3.1 B). The difference in number of PhoR and PhoB orthologs results from the
Capra 1106
A
B
Pho pathways per genome
100
coilfischei
V.
6
E.
9
50
P
4
40
9.1
20.
554
98
*
2_'VGY~v
S. oneidensis
100
-Y
PhoB
PhoR
aeruglnosafl
B. thallandensls
R. solancaerum
EX
4
M.
.magneticum
t4
s.b
S. maeiron
R. sphaeroides
lIMicu
... fr-
1
jtihi
Z mobills
0
0sulturreducens
B.sutlls
0.025
::
2
4
E
6
all
P
.slnceu
)
hdness(
0
tI
i~i_
C
E. coli(y)
S. oneidensis(y)
V. fischerl(y)
P. aeruginosa (y)
0.24
0
2
2
0
500
1000
0
Time (s)
500
C1
500
1000
0
500
Time (s)
Time (s)
M. magneticum ()
C. crescentus ((t)
0
0
1000
Time (s)
0.1
S. mellloti(u)
1000
B. thailandensis(p)
041
R. solanacaerum(11)
0.41
0.2
0.2
0
R. sphaeroides((x)
1.0
0.1
0.5
0.1
500
Time (s)
1000
500
1000
Time (s)
0
500
Time (s)
1000
0
500
Time (s)
1000
0
500
1000
1000
Z. mobilis ((t)
C.crescentus PhoR
0.2
Time (s)
500
Time (s)
0
(a)
:E coi PhoR (y)
a.
0
0
500
Time (s)
1000
Figure 3.1 Phosphotransfer specificity of PhoR is different in aproteobacteria.
and y-
(A) Percentage of genomes harboring one or two Pho pathways. (B) Neighbor-joining tree for a
subset of PhoR orthologs and sequence logos for specificity residues in PhoR and PhoB
orthologs. Logos are shown for orthologs in each subdivision and as a combined set. Bootstrap
values are out of 1000. A neighbor-joining tree for PhoB orthologs and a species tree for the
species used are in Figure 3.1A-B. (C) Time-courses of phosphotransfer from C. crescentus
PhoR (a) and E. coli PhoR (y) to each of 11 PhoB orthologs from representative a-, y-, and Pproteobacteria as noted above each graph. Band intensities for each PhoB were normalized in
each experiment to the initial amount of autophosphorylated kinase. Values for PhoB
phosphorylation can be greater than one as ATP was in excess in the reaction, allowing for reautophosphorylation of PhoR and subsequent transfer to PhoB. For original gel images, see
Figure 3.2D.
independent identification of kinase and regulator orthologs; most organisms encode both
PhoR and PhoB.
The specificity residues of both PhoR and PhoB are generally well-conserved (Figures
3. 1B, 3.2C), although several positions showed substantial variability. We then split the
Capra 1107
A
a
.a&uIf
e
-. cnema
P. Mawihwa
a
bndeminWW
aP. MW~o
nsenow
& OUhmdmene
SM
,t
,a.umn.n
C.C.mesae
it a
-
Z ab
z MtON"a
a aMn"ame
a Of vaet
m*.sssns
ft
C
loop
a4wW2X
Ui A~
Oli2fYA~k W41L
RL- VL~~
Rirv LVE
J2 BThTMYE
ct~
U4~QA
~&~fL~1
D
Y
f C-
V. bgnho,
.ft
ta
P. .mugiou. SLh
it
aOAMOM
*" 4.): .
C,Ovftin (a)
Ph"m
I
00-
E.
KOIT
-1.
1- .,,---,-- -
i
a
C. umfm £i
IMM(sa
a
nfamtuwa a..i
f spOm.mWuA.
Znwbab
.
8egg . S2
"emenho (a) W
.. 4....
:LOtJ
"W(Y
Ob. I
"
I-I
10
"we
- I 1,
,-001
I i4
1, -
Figure 3.2 Phylogenetic analyses of PhoR and PhoB.
(A) Neighbor-joining tree built using receiver domains of PhoB orthologs from the organisms
indicated. Bootstrap values are out of 1000. (B) Species tree for the species represented in the
gene trees of PhoR and PhoB. The species tree was obtained from microbesonline.org and built
using highly conserved genes that were likely vertically inherited. (C) Sequence logos for the DHp
domain of PhoR orthologs, split by clade or as a complete set. The DHp domain was divided into
Capra 1108
ca-helix 1, the loop region, and cc-helix 2 as the loop region is of variable length and aligns poorly.
Specificity residues in helix 1 are shaded. (D) Time courses of phosphotransfer from C.
crescentus and E. coli PhoR to a set of 11 PhoB orthologs. C. crescentus and E. coli PhoR
constructs were autophosphorylated and tested for phosphotransfer to each PhoB at the times
indicated. The species and proteobacterial subdivision from which each PhoB was taken are
indicated at the top. Quantifications are in Figure 2.1C.
PhoR and PhoB sequences into groups corresponding to the three major proteobacterial
subdivisions, cc, P, and y. Sequence logos built for each phylogenetic group revealed that
differences between subdivisions can account for nearly all of the variability in the
combined sequence logos (Figure 3.1 B). For instance, in y- and P-proteobacteria the first
two positions are almost always threonine and valine, whereas in u-proteobacteria these
positions are usually alanine and serine or two alanines. Similar observations were made
for the specificity residues of PhoB orthologs grouped according to phylogenetic
subdivision. Importantly, each PhoR and PhoB sequence logo was built using species that
are highly diverged. The strong conservation within each clade thus suggests that
specificity residues are usually subject to strong purifying selection. Why, though, have
specificity residues diverged between clades?
Identification of adaptive mutations that prevent cross-talk in vitro
The clade-specific differences in PhoR and PhoB specificity residues may simply reflect
degeneracy in the residues that enable PhoR and PhoB to interact. Alternatively, the
differences may have produced functional changes such that a PhoR from one clade is
less efficient at interacting with a PhoB from a different clade. To distinguish between
these
possibilities,
we
purified
PhoR
kinases
from
representative
y-
and
ca-proteobacteria, E. coli and C. crescentus, and examined their ability to phosphorylate a
panel of 11 PhoB orthologs from ax, P, and y-proteobacteria (Figure 3. 1C, 3.2D). For each
Capra 1109
PhoB from a y-proteobacterium, phosphotransfer from the E. coli (y) PhoR was
significantly faster than from C. crescentus (ct) PhoR. Similarly, each PhoB from an uproteobacterium was preferentially phosphorylated by the a-PhoR. For the two chosen
1-PhoB orthologs, we observed more rapid phosphorylation by the y-PhoR than the
ac-PhoR, consistent with the specificity residues of the P-PhoR and P-PhoB orthologs
being more similar to those found in y-proteobacteria than those in a-proteobacteria. We
conclude that within each proteobacterial subdivision, the phosphotransfer specificity of
PhoR and PhoB orthologs is relatively static. However, substitutions in the specificity
residues of c-PhoR and a-PhoB orthologs have led to significant differences in
phosphotransfer specificity between clades.
The changes in PhoR-PhoB specificity residues, and consequent alteration of interaction
specificity, could have resulted from neutral drift. However, the strong conservation of
specificity residues within each clade, which includes species that are widely divergent,
suggests that such drift is extremely rare. Instead, the alternative PhoR-PhoB specificity
residues in ca-proteobacteria may be adaptive and provide an important selective
advantage. We hypothesized that the substitutions in u-PhoR and ca-PhoB specificity
residues prevent unwanted cross-talk with another pathway that is specific to the ccproteobacteria, i.e. negative selection led to changes in a-PhoR and ca-PhoB. This model
predicts that PhoR orthologs from y-proteobacteria may phosphorylate response
regulators found exclusively in ca-proteobacteria, which the ca-PhoR orthologs have
adapted to avoid phosphorylating.
Capra I 110
A
C. crescentus(a) response regulators
8
---
K ~
N
OWO
WC--
~o ~o ~
N N
Mom
-
PhoR
"W"PqP"MPV"
E. coli(y)
I
PhoR
PhoR(T)
PhoR(V)
PhoR(Y)
NOW-
C. crescentus(a)
PhoR(TV)
PhoR(TY)
PhRIY
OPho R(TVY)
I--,
Am
ift
B
C. crescentus(a) response regulators
CIA M cc CM
s0
5
>=
)--- FJ
NO
(2
he
cc
N
PhoR
PhoR
PhoR(T)
PhoR(V)
PhoR(Y)
PhoR(TV)
PhoR(TY)
PhoR(VY)
PhoR(TVY)
0
E. col (y)
C. crescentus(a)
1.75
Figure 3.3 Substituting y-like specificity residues into a-PhoR increases
phosphorylation of NtrX.
(A) Phosphotransfer profiling of E. coli PhoR, C. crescentus PhoR, and C. crescentus PhoR
mutants containing y-proteobacterial specificity residues. Each autophosphorylated kinase,
indicated on the right, was incubated with each of 44 C. crescentus response regulators,
indicated across the top, for 15 minutes. (B) Quantification of profiles in panel A. Band intensities
for each response regulator were normalized to the level of autophosphorylated kinase and then
plotted relative to PhoB.
Capra I 111
C
A
NtrX
NtrY
0?GGA, L DoIVQAD
100
-
80
NtrC
NtrB
Ntr pathways per genome
0
"GGAQL
20
1
2
3
all
B
DSIVKAD TSER EGILEl
TPLSE:R III
2
D
NtrY
Time (a):
NtrX
2 1111
NtrB
2.0
2.0
1.6
1.6
1.2
1.2
E. cell (Y)
C. crexcentus (a)
C. cmscentus (a)
-PhoR(TV) C. crescentus (a)
-PhOR(TVY)
C. crescentus(a)
-PhoR
-PhoR
-PhoR(V)
NtrC
0
100
200
Time (s)
300
0
400
800
1200
1600
Time (s)
Figure 3.4 The divergent evolution of NtrX after duplication led initially to crosstalk with PhoR in a-proteobacteria.
(A) Percentage of genomes harboring one, two, or three Ntr pathways. (B) Time course of
phosphotransfer from C. crescentus kinases NtrY and NtrB to C. crescentus response regulators
NtrX and NtrC. The NtrY and NtrB constructs were autophosphorylated and examined for
phosphotransfer at the time points indicated. Error bars represent standard deviations, n=3. (C)
Sequence logos for specificity residues in NtrB-NtrC and NtrY-NtrX orthologs. Logos are shown
for orthologs in each subdivision and as a combined set. (D) Time course of phosphotransfer
from E. coli PhoR, C. crescentus PhoR, and C. crescentus PhoR mutants, listed in the legend, to
C. crescentus PhoB and NtrX. Error bars represent standard deviations, n=3.
To test this possibility, we performed comprehensive phosphotransfer profiling of E. coli
(y) and C. crescentus (a) PhoR. Both PhoR constructs were autophosphorylated in vitro
and then examined, in parallel, for phosphotransfer to the 44 response regulators encoded
by C. crescentus (Figure 3.3). Both PhoR constructs phosphorylated the C. crescentus
PhoB, consistent with their orthologous relationship; although as noted above,
phosphotransfer from the a-PhoR is more robust. Interestingly, the y-PhoR showed
significant phosphotransfer to NtrX, whereas the u-PhoR construct did not. Notably,
most Q-proteobacteria encode two paralogous Ntr systems, NtrB-NtrC and NtrX-NtrY,
while the y-proteobacteria typically encode only one, NtrB-NtrC (Figure 3.4A). The two
Capral 112
A
crescentus PhoR
ASY
TVF
C.
ASF
time(s):
PhoB D
TSF
9 2 § .
AVF
! R a
g @ 9 . 8
R a
AVY
TSY
§ . . g8
g
1
.e
?, 3 § .
TVY
E. coil PhoR
TVY
! g a
R8
AVY
TVY
E. coli PhoR
C. crescentus PhoR
ASF
NirX
TSF
AVF
1 I
TVF
.00
.01
1
ASY
TSY
I
TVY
~I--0 --
I
-~
C
2.0~
PhoR
PhoR
PhoR(T)
PhoR(V)
PhoR(Y)
PhoR(TV)
PhoR(TY)
PhoR(VY)
-
1.6
-
1.2
1.2
.
-
-
0
0
100
200
P):
hR a
C.
Ceii(y)
crescentus (a)
PhoR(TVY)
time (sec.)
time (sec.)
time (
IE
R
§ .
R a
?
e R
§
.
0.8
S0.4
PhoB
NtrX
CheYIV
KdpE
CtrA
CC0630
0.2
time(s):
0
9 8 9 .
AVF
S R
ALF
a I
NtrX
CheYIV
KdpE
CC0630
CtrA
100
200
300
time (sec.)
ADF
. g R a
PhoB
-
0
PhoR
ASF
-
AEF
ATF
!g 8 § . ?g 3 §
g g 8
PhoB No
G
PhoR
ASF
time($): .
NtrX
10
AVF
ALF
AEF
ADF
e
ATF
2
g g
I
E
~
I
,4
lll
0
Figure 3.5 Time courses of phosphotransfer from C. crescentus PhoR specificity
mutants.
(A-B) Time courses of phosphotransfer from E. coli PhoR, C. crescentus PhoR, and C.
crescentus PhoR mutants to either C. crescentus PhoB (A) or C. crescentus NtrX (B). For each
kinase the identities of specificity positions 1, 2, and 4 (see Figure 3.11B) are listed. Wild-type C.
crescentus PhoR has A, S, and F and wild-type E. coli PhoR has T, V, and Y. Kinase constructs
were autophosphorylated and then examined for phosphotransfer at the time points indicated.
Representative gels from three independent replicates are shown. Only the response regulator
band is shown. (C) Quantifications of phosphotransfers from panels A-B and replicates. Error
bars indicate standard deviations, n=3. (D) Time courses of phosphotransfer from PhoR(TV) to
the C. crescentus response regulators that were phosphorylated in the profile shown in Figure 2.
Only the response regulator bands are shown. Representative gels from three independent
experiments are shown. (E) Quantification of the phosphotransfers from panel D and replicates.
Error bars indicate standard deviations, n=3. (F-G) Time courses of phosphotransfer from C.
crescentus PhoR harboring various mutations at specificity position 2 to either C. crescentus
PhoB (F) or C. crescentus NtrX (G). Wild-type specificity residues for C. crescentus PhoR are A,
S, and F. Only the response regulator band is shown.
CapraI 113
c-Ntr systems, which likely arose through duplication and divergence, do not cross-talk
with each other in vitro (Figure 3.4B) and, consistently, have different specificity
residues (Figure 3.4C). Collectively, our observations suggest that the different PhoR
specificity residues seen in a-proteobacteria may have evolved to accommodate the
presence of a second, lineage-specific pathway, NtrX-NtrY. Such a change in PhoR was
presumably accompanied by changes in the PhoB specificity residues (see Figure 3.1B)
to maintain phosphotransfer from PhoR.
Thus, we hypothesized that the alanine, serine, and phenylalanine found at specificity
positions 1, 2, and 4 of u-PhoR proteins represent adaptive mutations that prevent crosstalk to NtrX. To test this hypothesis, we created a series of C. crescentus PhoR mutants in
which specificity residues were replaced with the corresponding residues from
y-proteobacterial PhoR. We made each single mutant, three double mutants, and the
triple mutant. Each mutant kinase was then profiled against the complete set of C.
crescentus response regulators to examine what effect, if any, these residues have on
phosphotransfer specificity. Strikingly, each mutant led to a significant increase in NtrX
phosphorylation (Figure 3.3). We also examined detailed time courses of phosphotransfer
from each mutant PhoR, as well as the wild-type kinases, to the C. crescentus regulators
PhoB and NtrX. Each mutant kinase exhibited an increase in cross-talk with NtrX
compared to the wild-type C. crescentus (c)
PhoR, but retained the ability to
phosphorylate C. crescentus PhoB at rates comparable to the wild-type PhoR (Figures
3.4D, 3.5A-C). Although some mutant PhoR kinases phosphorylated several substrates
(see Figure 3.3), we focused on PhoB and NtrX as time-courses of phosphotransfer
indicated these as the two preferred targets of mutant PhoR constructs (Figure 3.5D-E).
Capra I 114
The most significant cross-talk to NtrX occurred for PhoR mutants with a valine
substituted for serine at specificity position 2. Importantly, substantial cross-talk was not
observed when this serine was substituted with other residues including leucine,
aspartate, glutamate, and threonine. Only valine, corresponding to that found in yproteobacterial PhoR orthologs, produced significant cross-talk (Figure 3.51F-G).
Taken together, our in vitro studies support the notion that alanine, serine, and
phenylalanine at specificity positions 1, 2, and 4 represent adaptive mutations that
prevent cross-talk to NtrX in a-proteobacteria.
Avoidance of cross-talk is a significant selective pressure
To test whether these mutations also prevent cross-talk in vivo, we engineered the
chromosomal copy of phoR in the o-proteobacterium C. crescentus to produce a mutant
PhoR in which specificity positions 1 and 2 are threonine and valine, respectively, as they
are in y-proteobacteria; hereafter this mutant strain is referred to as PhoR(TV). Based on
our in vitro experiments, we expected that cross-talk from PhoR(TV) to NtrX would be
induced during growth in phosphate-limited media (Figure 3.6A). During growth in such
conditions, wild-type PhoR is stimulated to autophosphorylate and phosphotransfer to
PhoB, which then activates genes involved in responding to phosphate limitation. Thus,
any effects of increased cross-talk to NtrX by the PhoR(TV) kinase should be manifest
specifically during growth in phosphate-limited media. We grew cells to mid-logarithmic
phase in phosphate-limited media and measured the rate of growth by monitoring the
accumulation of optical density at 600 nm. In minimal media containing either 50 [M
phosphate or 5 1 M phosphate, the PhoR(TV) mutant grew significantly more slowly than
Capra 1115
C
A
NtrY
PhoR
Phosphate-limited
PhoR(TV)
WT
25
H~P
H~P
Phosphate-replete
50
NtrY
PhoR
- WT
10
IDP
PhoB
E
E
~Pl
D~P
NtrX
PhoB
5
5
D~P
NtrX
-
AphoR
-
PhoR(TV)
PhoR(TV)/AntrX
AntrX
10
0
B
20
40 50 80
Time (hrs)
100
0
20
40
50
50
100
Time (hrs)
D
Relative doubling time
0.6
0.8
1.0
1.2
1.4
5
1.6
SB
B
PhoR(TV)
WTT
AphoR
AphoR
E
0
AntrX
log 2 (mutant
E
PhoR(TV)/AntrX
0
v. WT): c
PhoR(TV)
WT
Time (s): 0
PhoR(TV)
30 60 90 300
0
NtrY
30 60 90 300
AphoR
NtrXAC
AntrX
a
PhoR(TV)
PhoR(TV)/AntrX I
NtrXAC-P
-
Figure 3.6 Cross-talk between PhoR(TV) and NtrX leads to a growth defect and
fitness disadvantage in phosphate-limited media.
(A) Schematic of strains examined. In the wild type, PhoR-PhoB and NtrY-NtrX are insulated,
whereas the PhoR(TV) mutant leads to cross-talk between PhoR and NtrX. (B) Doubling times of
C. crescentus strains AphoR, AntrX, PhoR(TV), and PhoR(TV)/AntrX relative to wild type in M5G
(phosphate-limited) and M2G (phosphate-replete) media. Error bars indicate standard errors,
n=3. For growth curves in M8G medium (5 [M), see Figure 3.7A-B. (C) Wild type, AphoR, AntrX,
PhoR(TV), and PhoR(TV)/AntrX were each competed against the wild type in M2GX and M5GX.
The percentage of mutant cells in the population was measured periodically for 104 hours.
Curves represent the average of two independent competitions with swapped fluorophores. Also
see Figure 3.7C-D. (D) Expression data for known members of the pho regulon in PhoR(TV) and
AphoR in M2G (phosphate-replete) media. Data are expressed as log 2 values of the ratio
between a given mutant and wild-type C. crescentus, and are color-coded according to the
legend. (E) Time courses of phosphotransfer from kinases PhoR(TV) and NtrY to the regulators
NtrXAC and an NtrXAC harboring p-like specificity substitutions. Only the response regulator
band is shown.
wild type, with a doubling time ~30% longer than wild type in each case (Figures 3.6B,
3.7A-B). This growth defect was almost as severe as that observed for a AphoR strain
which cannot mount a proper transcriptional response to phosphate-limitation. To assess
whether cross-talk from PhoR(TV) to NtrX contributed to the slow growth phenotype
Capra 116
A
B
Relative doubling time
0.6
0.18-
0.16-
1.2
1.4
1.6
0.14-
AphoR
WT
AphoR
-
V
0.
PhoR(TV)
PhoR(TV)/AntrX
AntrX
PhoR(TV)
AntrX
-
PhoR(TV)/AntrX
0
z
1.0
WT
8
0
0.8
0.12-
*5
'000
6
8
7
10
Time (hrs)
C
WT-YFP: mutant-CFP
WT-CFP: mutant-YFP
50
phosphate-limited
medium
.
25
25
10
10
M
5
E
A
WT
.
-
AphoR
-
PhoR(TV)
PhoR(TV)AntrX
AntrX
1
0
phosphate-replete
medium
20
40 60 80
time (hrs)
100
50
50
25
25
10
10
0
20
40 60 80
time (hrs)
100
0
20
40 60 80
time (hrs)
100
E
S
5
1
.7
5
20
40 60 80
time (hrs)
100
phosphate-limited
D
a
-2
phosphate-replete
-0.0018
-0.0048
-
*
-0.0014
-0.0026
-0.0172
_W WT
-AphoR
U
U
-0.0731
-4
-0.1272
-0.1326
-2
-a- PhoR(TV)
-W- PhoR(TV)/AntrX
-0- AntrX
.4
E
-6
-0.1412
0
-6
0
-8
10
20
30
time (generations)
40
0
10
20
30
40
50
-0.1580
time (generations)
Figure 3.7 The specificity substitutions AS--+TV in C. crescentus PhoR lead to a
selective disadvantage in phosphate-limited media.
(A) Growth curves for wild type, AphoR, AntrX, PhoR(TV), and PhoR(TV)/AntrX in M8G, which
contains 5 [M phosphate. Data points represent the average of 3 replicates. (B) Relative
doubling times calculated for the growth curves in panel A. Error bars represent standard error,
n=3. (C) Wild type, AphoR, AntrX, PhoR(TV), and PhoR(TV)/AntrX were each competed against
the wild type in M2GX (phosphate-replete) and M5GX (phosphate-limited) for 104 hours. One set
of competitions used YFP-labeled wild type and CFP-labeled mutant cells, whereas the other
used CFP-labeled wild type and YFP-labeled mutant cells, as indicated at the top. Growth
medium is listed to the left. The identity of the mutant cells for each competition is shown in the
legend. (D) The average values of the competitions shown in panel C, plotted as
log2(mutant/wild-type) against the number of wild-type generations in each medium. Best-fit lines
for each competition are shown. The selective coefficients, per generation, are listed on the right
Capra I 117
side of each graph.
observed, we deleted ntrX in the PhoR(TV) strain. Indeed, the deletion of ntrX
significantly reduced the growth deficiency of the PhoR(TV) mutant (Figures 3.6B, 3.7AB) suggesting that cross-talk with NtrX contributes significantly to the slow growth
phenotype of a PhoR(TV) strain. The suppression observed was not a non-specific
acceleration of growth as the ntrX deletion alone had no effect on growth in phosphatelimited medium. In phosphate-replete medium, the PhoR(TV) mutant strains grew at a
rate nearly identical to the wild type (Figure 3.6B), indicating that, as expected, cross-talk
to NtrX requires PhoR to be activated as a kinase. The ntrX deletion and
PhoR(TV)/AntrX strains grew more slowly in phosphate-replete medium, as the NtrYNtrX pathway is likely necessary for responding to a signal or metabolite produced in
M2G medium.
To corroborate our growth rate measurements, we performed competitive fitness assays
in which each mutant strain was mixed with the wild type at a ratio of 1:1 and grown in
the same flask for 104 hours, or approximately 40 wild-type generations. The mutant and
wild-type strains were engineered to constitutively produce CFP or YFP, allowing for a
rapid assessment of relative strain abundance using fluorescence microscopy. In
phosphate-limited
conditions, the PhoR(TV) strain showed a significant growth
disadvantage, being almost completely eliminated from the population after 104 hours
(Figures 3.6C, 3.7C). The fitness disadvantage of the PhoR(TV) mutant was comparable
to that of AphoR competed against wild type in the same phosphate-limited medium.
Consistent with our growth measurements, deleting ntrX in the PhoR(TV) background
Capra I 118
improved competitive fitness (Figures 3.6C, 3.7C-D). In phosphate-replete conditions,
the PhoR(TV) and AphoR mutants retained a ratio with wild type close to 1:1,
demonstrating that the selective disadvantage of introducing ancestral specificity residues
into PhoR likely occurs only in conditions in which PhoR is a kinase. Collectively, these
data further support a model in which the u-specific substitutions in PhoR specificity
residues (T->A and V--S at specificity positions 1 and 2) are selectively advantageous
because they help prevent phosphotransfer cross-talk to NtrX, and perhaps other response
regulators.
The growth and competitive fitness defects of PhoR(TV) in phosphate-limited media
were comparable to that seen for AphoR. This similarity suggested that the detrimental
effect of cross-talk in the PhoR(TV) strain stems from an inability to phosphorylate PhoB
and activate PhoB-dependent genes in phosphate-limited conditions. To test this
hypothesis directly, we examined global gene expression patterns in the PhoR(TV) and
AphoR strains during growth in phosphate-limited conditions. These expression profiles
exhibited strong similarity with a Pearson correlation coefficient of ~0.9, supporting a
model in which phosphorylation cross-talk from PhoR(TV) to NtrX comes at the expense
of phosphorylating PhoB. The inappropriate phosphorylation of NtrX could also
contribute to the growth defect of the PhoR(TV) mutant. However, NtrX-dependent
genes (see Materials and Methods) were not significantly affected in the PhoR(TV) strain
during growth in phosphate-limited conditions; NtrX-dependent genes behaved similarly
in the PhoR(TV) and AphoR strains in phosphate-limited conditions. This may result
from NtrY, the cognate kinase for NtrX, functioning as a phosphatase to prevent the
accumulation of phosphorylated NtrX in phosphate-limited media. Consistent with this
Capra| 119
notion, ntrX and ntrY are not required for growth in phosphate-limited media, suggesting
that in this condition NtrY is likely in a phosphatase state.
Importantly, and in contrast to NtrY, PhoR functions as a kinase, not a phosphatase, in
phosphate-limited media. Thus, our results indicate that the c-specific substitutions in
PhoR specificity residues (T-+A and V-+S) impact fitness by affecting cross-talk at the
level of phosphotransfer. Consistently, in phosphate-replete media, when PhoR is
primarily active as a phosphatase, these substitutions had little to no effect on competitive
fitness (Figure 3.6B-C, 3.7C-D). To further confirm that these substitutions do not
significantly impact the phosphatase activity of PhoR, we examined global patterns of
gene expression in the PhoR(TV) mutant grown in a phosphate-replete medium. Under
these conditions, PhoR likely acts as a phosphatase to eliminate any errant
phosphorylation of PhoB. Accordingly, the expression levels of known PhoB-dependent
genes, such as pstC, pstA, and pstB, were modestly elevated in a AphoR strain grown in
phosphate-replete medium (Figure 3.6D). By contrast, these genes were not affected, or
were slightly downregulated, in the PhoR(TV) strain grown in the same phosphatereplete conditions, indicating that PhoR(TV) retains phosphatase activity in vivo.
Collectively, our data demonstrate that the growth and fitness defect of the PhoR(TV)
mutant stems from inappropriate phosphotransfer to NtrX, and perhaps other non-cognate
substrates.
Capra 1120
Different adaptive mutations prevent cross-talk in other proteobacterial
clades
Our results suggest that u-proteobacteria have accumulated substitutions in PhoR that
prevent unwanted cross-talk with the non-cognate substrate NtrX. There could, however,
be other ways to avoid cross-talk between these systems in other clades. Like the caproteobacteria, most P-proteobacteria encode NtrY-NtrX orthologs (Figure 3.4C).
However, the 1-PhoR orthologs have specificity residues at positions I and 2, similar to
those found in y-PhoR orthologs. This observation suggests that either the
1-
proteobacteria can tolerate cross-talk between PhoR and NtrX, or other mutations have
emerged to prevent PhoR from phosphorylating NtrX. We favored the latter possibility as
a comparison of sequence logos for the NtrX orthologs from cx- and P-proteobacteria
revealed differences at two critical positions (Figure 3.4C). Whereas most c-NtrX
orthologs have aspartate, glycine, and lysine at specificity positions 2, 5, and 7,
respectively, the P-NtrX orthologs typically have glycine, glutamate, and alanine at these
same three respective positions. We speculated that the different specificity residues in a
given P-NtrX may eliminate cross-talk from a j-PhoR; that is, f-proteobacteria may have
evolved to avoid cross-talk by accumulating substitutions in NtrX rather than PhoR and
PhoB.
To test this hypothesis, we asked whether introducing the P-NtrX specificity residues into
an c-NtrX would eliminate cross-talk from ca-PhoR(TV) which, as shown above,
phosphotransfers to a-NtrX in vitro and in vivo. Indeed, whereas C. crescentus NtrX was
robustly phosphorylated by PhoR(TV), a mutant NtrX harboring the
P-like
substitutions
Capra 1121
A
B
CusS
4
TNTQEI
YedV
NAGQQV
2
QseC
CpxA
BasS
BaeS
PhoQ
RstB
EnvZ
PhoR
KdpD
CreC
YfhK
TAVGEV
TRLGAL
AGLHEL
0
AVGEEA
AVSTRS
VRYREM
TRLAEM
TVGYEM
TVGQEI
AAGAEI
ASEGEL
ZraS
NtrB
SSGLKY
GGGAQL
AtoS
DpiB
TAGYQI
STGLQM
LSKMVS0
LSRILT
ITRTAG
NTAVRR
NASSRL
NarX
NarQ
UhpB
YehU
YpdA
:
C
ed,
u
dp
.
h
Figure 3.8 Extant two-component signaling pathways are insulated from each
other at the level of phosphotransfer.
(A) The six primary specificity residues are shown for each of the 22 canonical E. coli histidine
kinases. Hybrid histidine kinases and the non-canonical kinases DcuS and CheA were omitted.
The histidine kinases are separated into groups by color based on the family of their cognate
response regulator: pink, OmpR/winged helix-turn helix; green, NtrC/AAA+ and Fis domains;
blue, NarL/GerE helix-turn-helix; brown, LytR. For specificity residues from E. coli response
regulators and C. crescentus histidine kinases and response regulators, see Figure 3.9. (B)
Sequence logo for the specificity residues in panel A. (C) A qualitative two-dimensional
representation of the distribution of E. coli histidine kinases in the sequence space defined by the
six primary specificity-determining residues. Each oval represents the set of response regulators
recognized by a histidine kinase given its specificity residues. Spheres are colored using the
same scheme as in panel A. With the exception of NarQ and NarX (see text), the spheres are
non-overlapping, indicating a lack of cross-talk in vivo and in vitro. Kinases were placed relative to
one another based roughly on their ability to phosphorylate the cognate regulators of other
histidine kinases after extended incubation times in vitro (Skerker et al., 2005; Yamamoto et al.,
2005). For example, CpxA shows a strong preference for phosphotransfer to its cognate regulator
CpxR, but will phosphorylate the cognate regulators of EnvZ and RstB after extended periods of
time.
D13G, G20E, F1071, and K108A was not detectably phosphorylated (Figure 3.6E). This
mutant NtrX was not simply unfolded or unphosphorylatable as it was still robustly
phosphorylated by ca-NtrY. Hence, the substitutions introduced specifically eliminated
Capra 1122
A
C. crescentus
canonical histidine kinases
CC1063
CC0238
CC0289
CC0530
CC1181
CC1294
CC1305
CC1594
CC2765
CC2932
CC3327
CC1740
CC1742
CC0759
CC0248
CC2482
CC0586
CC1062
CC2755
CC2884
(DivJ)
NAGFDI
TSSAET
(PhoR)
(CenK)
ASGFET
TSMADR
TRFREA
TAGEEV
AAAQRR
(KdpD)
STGATT
SVTESQ
TRLEAM
TSALAD
(NtrB)
(NtrY)
(FixL)
(PleC)
AGGAQL
TPLSER
SANLTG
ATVVRE
NAGFEI
TSGFEQ
NAGFEI
TRAREV
NAGFSV
B
C. crescentus
response regulators
CC0284
CC0432
CC0437
CC0440
CC0588
CCO591
CC0596
CCO630
CC0744
CC2463
CC2576
CC3015
CC3258
CC3286
CC3471
CC0237
CC0294
CC1182
CC1293
CC1304
CC1595
CC2757
CC2766
CC2931
CC3035
CC3325
CC3743
CC0909
CC1741
CC1743
CC3315
CC0758
CC1150
CC0247
(LovR)
(CheYI)
(CheYII
(CheYII I)
(CheYIVT)
(CheYV)
(CheYVI
(CpdR)
(DivK)
STMMMAN
QTMLNAT
NPISQVT
DAILGVE
YTTIGLS
SVIVRMD
ELVMDMN
DSLFRAH
NLNLDLS
ELVEALS
ELVLDMR
NGFLQIS
DVLIITT
(PhoB)
SVIVRVD
DNISLAS
EALLYNS
DGIVDFN
DRVFRGS
DVVDKAE
(KdpE)
EQIFPAG
DEAAHGA
DDLGLAH
(PetR)
(CtrA)
DRLLEFE
DATTLMH
DSHLSVQ
(CenK)
(FlbD)
(NtrC)
(NtrX)
(TacA)
(FixJ)
(SpdR)
CC1767
CC0612
CC3477
CC0436
CC0597
CC2462
CC1364
CC2249
CC3100
CC3155
ELLEHLS
(NasT)
(PhyR)
(CheBI)
(CheBII)
(PleD)
DDLALAR
LGQVKMV
DSIVQAD
EDILGIK
DTQLAVS
DSASFLS
EQKLLSL
C
E. coil
response regulators
CheY
CusR
YedW
QseB
CpxR
BasR
BaeR
PhoP
RstA
OmpR
PhoB
KdpE
CreB
TorR
ArcA
YfhA
ZraR
NtrC
AtoC
DpiA
NarL
NarP
UhpA
UvrY
RcsB
EvgA
DcuR
FimZ
YehT
YpdB
CheB
FTMINLT
EKTYKGA
NRTWQGS
DLIGTGA
DELLELN
DLLGLAA
EKLLDYS
NLLHVQH
DEVLAYP
DRLLRYN
EPIMFVS
EAIFTAG
EGITYMS
EVTRSYE
EVTTSIN
DGLLLRD
DSHIALD
DSIVRAD
ENVMTAD
EPLMEYA
HMLGQLE
HLMGQLD
HIVGQLS
HLVGRIA
HIVHKSA
HLAANLG
DMVLRYQ
HIISVLD
ELANVFD
ELAEWLI
SLMIEIL
DPLRRAD
DKFRTSN
PFSHRRV
EVIDALQ
STMLAAD
SVVMRWA
IANLAKD
NNMVTMT
NHIIAIT
NATLEHN
NHMLEMT
Figure 3.9 Orthogonality of specificity residues in E. coli and C. crescentus twocomponent signaling proteins.
(A-C) The specificity residues of (A) all canonical histidine kinases from C. crescentus, (B) C.
crescentus response regulators, or (C) E. coli response regulators. The text for residues are
colored based on the sub-family of response regulators or, in the case of kinases, by the subfamily of its cognate response regulator, if known: red, receiver domain only; pink, OmpR/winged
helix-turn helix; green, NtrC/AAA+ and Fis domains; blue, NarL/GerE helix-turn-helix; light green,
ActR; grey, AmiR; navy, PhyR; orange, CheB/methyltransferase; purple, GGDEF; brown, LytR;
black, no known cognate for the histidine kinase or no identified sub-family for the response
regulator.
Capra 1123
cross-talk from PhoR(TV), while still allowing for interaction with the cognate kinase
NtrY. Taken together, these results suggest that in P-proteobacteria, substitutions in NtrX
alleviated cross-talk with PhoR while in c-proteobacteria substitutions in PhoR prevented
cross-talk with NtrX. Although the substitutions are different, the net result in both cases
was an insulation of the Ntr and Pho systems.
Global optimization of signaling fidelity
Our results with the Pho and Ntr signaling pathways indicate that the avoidance of crosstalk following gene duplication is a major selective pressure that drives the accumulation
of adaptive substitutions in the specificity-determining residues of two-component
signaling proteins. More generally, this model predicts that the specificity residues of
two-component signaling proteins in extant organisms should be sufficiently different
from, or orthogonal to, one another to prevent cross-talk. To test this prediction, we
extracted the six major specificity residues from each of the 22 canonical histidine
kinases encoded in the E. coli K12 genome (Figure 3.8A). Pairwise comparisons
indicated that kinases typically had no more than three identities with every other kinase
at these six specificity sites, often with non-conservative differences at the remaining
sites. One notable exception is NarX and NarQ, which contain two identities and four
conservative differences. However, these kinases, which likely arose through gene
duplication, each phosphorylate the response regulators NarL and NarP in vitro and likely
in vivo, and hence represent a case of physiologically beneficial cross-regulation (Noriega
et al., 2010). Aside from these two kinases, there is a general pattern of orthogonality
between specificity residues in the system-wide set of E. coli histidine kinases. This
orthogonality is further reflected by a lack of information in a sequence logo built from
Capra 1124
the specificity residues of the 22 E. coli histidine kinases (Figure 3.8B), particularly in
comparison to the sequence logos built from orthologous histidine kinases (Figures 3. 1B,
3.4C). A similar pattern of orthogonality was evident in the specificity residues of the 20
canonical histidine kinases in C. crescentus, as well as the specificity residues of the
response regulators from both F. coli and C. crescentus (Figure 3.9). These observations,
in combination with our detailed investigation of the Ntr and Pho proteins across
phylogenies, suggest that the avoidance of cross-talk is a pervasive and significant
selective pressure driving the system-wide insulation of two-component signaling
pathways, and consequently, that in extant organisms, two-component systems are
largely insulated from one another (Figure 3.8C).
Capra 1125
Discussion
Signaling protein families, in both prokaryotes and eukaryotes, frequently expand
through gene duplication (Ohno, 1970; Pires-daSilva and Sommer, 2003). The retention
of the duplicated genes often requires mutations that insulate them from one another,
allowing each to transmit signals without inducing cross-talk. This divergence process
may be additionally constrained by a need to avoid cross-talk with other, existing
members of the same protein family. For two-component pathways, the duplicationdivergence process can be conceptually framed by considering the sequence space
defined by the specificity-determining residues of histidine kinases (Figures 3.9-3.10).
For each kinase, these residues dictate the substrates it can phosphorylate, with different
kinases recognizing largely non-overlapping, or orthogonal, sets of substrates. Gene
duplication leads initially to a complete overlap and requires that one or both of the
duplicates accumulate changes in its specificity residues, thus separating them in
sequence space (Figure 3.10).
The mutational path taken by a given kinase may cause it to infringe on the sequence
space occupied by another kinase, as was likely the case with the Ntr and Pho systems in
a-proteobacteria. Such overlap then necessitates additional mutations to achieve a
system-wide optimization of specificity. Our results indicate that such optimization and
the avoidance of cross-talk are important selective pressures influencing two-component
systems and they can drive the divergent evolution of orthologous proteins.
How did the NtrY-NtrX pathway arise if cross-talk is detrimental? Although we cannot
infer the order of events with complete certainty, a plausible scenario is that the NtrY-
Capra 1126
NtrB
ancestral state,
pre-duplication
Am
PhoRO
NtrB
gene duplication
N rrt
PhoR
NtrB
divergence and
cross-talk elimination
NtrY
PhoR
NtrB
derived state,
post-duplication
NtrY'
A
W
1
PhoR
Figure 3.10 Adaptive divergence of duplicated signaling pathways involves the
elimination of cross-talk.
Ovals represent the set of response regulators recognized by a histidine kinase, as determined
by its specificity residues (see also Figure 3.8). The NtrB-NtrC pathway is shown duplicating to
produce the paralogous system NtrY-NtrX. As these pathways diverged, the specificity of NtrY
overlapped that of PhoR, necessitating a change in PhoR specificity to yield the derived state with
insulated pathways.
NtrX pathway arose during growth in phosphate-replete conditions where it provided a
selective advantage, as suggested by the slow growth of a AntrX strain in these
conditions. Subsequent growth in phosphate-limited conditions would then select for
strains that have accumulated mutations eliminating cross-talk between PhoR and NtrX.
We showed that such insulation can occur with only one or two point mutations,
Capra 127
supporting the plausibility
of this scenario in an ancestral ca-proteobacterium.
Interestingly, the P-proteobacteria likely followed a different mutational path to avoiding
cross-talk, accumulating substitutions in NtrX rather than PhoR. The difference between
the two clades of proteobacteria may reflect the inherent stochasticity of mutations and
selection. Alternatively, the growth conditions or genomic context of the ancestral
organisms in which gene duplication occurred may have deterministically influenced
selection.
In sum, we propose that the evolution of two-component signaling genes is characterized
by long periods of stasis with specificity-determining residues subject to strong purifying
selection to ensure robust phosphotransfer from kinase to regulator. Gene duplication, or
lateral transfer events, can disrupt this stasis, requiring a global re-optimization of
existing signaling proteins to accommodate the new pathway. The specificity residues are
thus likely subject to bursts of diversifying selection; however, these residues would not
necessarily exhibit commonly used signatures of diversifying selection such as large
dN/dS values. Instead, our work emphasizes that a molecular-level understanding of
protein evolution and the identification of adaptive mutations ultimately demands an
integration of sequence analysis with focused biochemical and genetic characterizations.
Our approach and findings are relevant beyond two-component signaling as paralogous
signaling protein families are found throughout biology. In fact, most organisms use a
remarkably small number of types of signaling protein to carry out their diverse
information-processing tasks. In all cases, duplication and divergence is a primary means
by which new pathways are created and, consequently, issues of specificity and the
fidelity of information transfer are critical. While eukaryotes sometimes rely on tissueCapral 128
specific expression of paralogous genes or spatial mechanisms like scaffolds to enforce
specificity, many common signaling proteins and domains, such as PDZ, SH3, SH2, and
bZIP proteins (Hou et al., 2009; Liu et al., 2011; Newman and Keating, 2003; Stiffler et
al., 2007; Tonikian et al., 2008; Zarrinpar et al., 2003), rely on molecular recognition and
a relatively small set of specificity-determining residues. Hence, our observation that
pathway insulation in bacteria can be achieved with a limited number of mutations may
help to explain how organisms in all domains of life have exploited gene duplication to
expand and diversify their signaling repertoires.
Capra 1129
Materials and Methods
Identification of orthologs and construction of gene trees
A modified version of reciprocal best blast hits was used to identify orthologous proteins.
For E. coli PhoR, the DHp domain was used as a query in BLAST searches against fully
sequenced bacterial genomes in GenBank (September 2009). The top ten hits from each
genome were then subjected to reciprocal BLAST searches against the E. coli MG1655
genome. If only the top hit identified E. coli PhoR as the best match, it was called as a
PhoR ortholog. If multiple hits identified E. coli PhoR as the best match, the top hit was
called as an ortholog and additional hits were evaluated as follows. If an additional hit
had an E-value within 103 of the top hit and was closer to the top hit than to the fifth hit
(which generally had an E-value reflecting the overall paralogous relationship of histidine
kinases), we also called it as an ortholog of E. coli PhoR and examined the next hit
similarly. For genomes with more than one hit called as an ortholog, duplications were
inferred and each hit deemed a member of the PhoR orthogroup. A similar procedure was
followed to identify orthologs of PhoB, NtrB, NtrC, NtrX, and NtrY using as query
sequences the E. coli PhoB receiver domain, the C. crescentus NtrB and NtrY DHp
domains, or the C. crescentus NtrC and NtrX receiver domains.
Orthologous sequences were aligned using ClustaiX (Chenna et al., 2003). Sequence
logos for the specificity residues, extracted from the aligned sequences, were built using
WebLogo (Crooks et al., 2004). To help correct for phylogenetic biases in genome
sequencing efforts, sequences were filtered to ensure that no two sequences were more
than 95% identical.
Capral 130
PhoR DHp domains and PhoB receiver domains were extracted using HMMER with
models for a HisKA domain or REC domain, respectively (Wistrand and Sonnhammer,
2005), and used to build gene trees through the PHYLIP package (Felsenstein, 1989)
using the neighbor-joining algorithm provided. The tree was rooted using B. subtilis
PhoR as the outgroup. Reported bootstrap values are out of 1000.
For genome-wide analyses of specificity residues, only canonical histidine kinases were
included. Canonical kinases were defined as those containing the PFAM HisKA domain
and no REC domain.
Growth conditions and strain construction
C. crescentus cells were grown at 30'C in PYE, M2G (10 mM phosphate), M5G (50 iM
phosphate), or M8G (same as M5G but with 5
necessary with oxytetracycline (1
xM phosphate), supplemented when
tg/ml), kanamycin (25 [tg/ml), 0.2% glucose or 0.3%
xylose. E. coli strains were grown at 37*C in LB supplemented with carbenicillin (100
tg/ml) or kanamycin (50 [tg/ml). Transductions were performed using (PCr30 (Ely,
1991).
Table 3.1 -
Strains and plasmids
Name
E. coli
BL21-tuner
DH5a
C. crescentus
CB15N
Description
Source
E. coli strain for protein expression and purification
E. coli general cloning strain
Novagen
Invitrogen
synchronizable derivative of wild-type CB15
(Evinger
and
Agabian,
1977)
Capra 1131
ACC0289
AphoR
ACC1743
AntrX
ML1934
PhoR(TV)
ML1935
PhoR(TV) AntrX
ML1936
Pxy-yfp-xyX
ML1937
Pxy-cfp-xyX
ML1 938
PhoR(TV) Pxyrcfp-xyX
ML1939
PhoR(TV), Pxyr-yfp-xylX
ML1940
AphoR Pxyrcfp-xyX
ML1941
AphoR Pxyr-yfp-xyIX
ML1942
AntrX Pxy-cfp-xyX
ML1 943
AntrX Pxy-yfp-xyIX
ML1 944
PhoR(TV) AntrX Pxy-cfp-xyX
ML1 945
PhoR(TV) AntrX Pxvr-yfp-xyX
General purpose vectors
pENTR/D-TOPO
ENTRY vector for Gateway cloning system (kanR)
pML310
Destination vector, TRX-HIS6 (kan R)
pML333
Destination vector, HIS -MBP
(kan R)
6
pNPTS138
integration vector (sacBs, kanR)
pXCFPN-4
Pxy-cfp
pXYFPN-4
Plasmids
pXCFPN-4:Pxy-cfp-xy/X
pXYFPN-4:Pxyr-yfp-xy/X
pNPTS138:Pxyryfp-xyX
pNPTS138:Pxy-cfp-xyX
Pxvl-yfp
intermediate cloning plasmid
intermediate cloning plasmid
integration of YFP behind the xylose promoter
integration of CFP behind the xylose promoter
allelic replacement of C. crescentus phoR with
pNPTS138:PhoR(TV)
phoR(TV)
Protein expression plasmids
pML333:PhoRCc
C. crescentus HIS 6-MBP-PhoR
pML333:PhoR(T)_Cc
C. crescentus HIS 6-MBP-PhoR(T)
pML333:PhoR(V)_Cc
C. crescentus HIS 6-MBP-PhoR(V)
pML333:PhoR(Y))_Cc
C. crescentus HIS 6-MBP-PhoR(Y)
pML333:PhoR(TV)_Cc
C. crescentus HIS 6-MBP-PhoR(TV)
pML333:PhoR(VY)_Cc
C. crescentus HIS 6-MBP-PhoR(VY)
pML333:PhoR(TY)Cc
C. crescentus HIS 6-MBP-PhoR(TY)
pML333:PhoR(TVY)_C
C
C. crescentus HIS 6-MBP-PhoR(TVY)
pML333:PhoREc
E. coli HIS 6-MBP-PhoR
pML333:NtrB
C. crescentus HIS 6-MBP-NtrB
pML333:NtrY
C. crescentus HIS 6-MBP-NtrY
C. crescentus TRX-HIS 6-NtrXAC(D13G, G20E, F1071,
pML31 0-NtrXAC-P
K108A)
(Skerker et
al., 2005)
(Skerker et
al., 2005)
this study
this study
this study
this study
this study
this study
this study
this study
this study
this study
this study
this study
Invitrogen
(Skerkeret
al., 2005)
(Skerkeret
al., 2005)
(Skerker et
al., 2005)
(Thanbichle
r et al.,
2007)
(Thanbichle
r et al.,
2007)
this
this
this
this
study
study
study
study
this study
this
this
this
this
this
this
this
study
study
study
study
study
study
study
this study
this study
this study
this study
this study
Capral 132
pML310:CC1741AC
pML310:CC1743AC
pML310:CC3743AC
pML310:b0399
pML310:VF1988
pML310:SO1558
pML31 0:PA5360
pML310:BTH12768
pML310:RSc1534
pML31 0:CCO294
pML310:amb1370
pML310:SMcO2140
pML310:RSP2599
pML310:ZMO1 164
C. crescentus TRX-HIS 6-NtrCAC
C. crescentus TRX-HIS6 -NtrXAC
C. crescentus TRX-HIS 6-CenRAC
E. coli MG 1655 TRX-HIS 6-PhoBAC
V. fischeri ESi 14 TRX-HIS 6-PhoBAC
S. oneidensis MR-i TRX-HIS 6-PhoBAC
P. aeruginosa PAOi TRX-HIS 6-PhoBAC
B. thallandensis E264 TRX-HIS 6-PhoBAC
R. solanacearum GM1OOO TRX-HIS 6-PhoBAC
C. crescentus CB 15 TRX-H IS 6-PhoBAC
M. magneticum sp AMB-1 TRX-HIS 6-PhoBAC
S. meliloti 1021 TRX-HIS 6-PhoBAC
R. sphaeroides 2.4.1 TRX-HIS 6-PhoBAC
Z. mobilis ZM4 TRX-HIS 6-PhoBAC
this study
this study
this study
this study
this study
this study
this study
this study
this study
this study
this study
this study
this study
this study
Strains used are listed in Table 3.1. To construct ML1934, PhoR(TV), a region from
nucleotide position -30 (relative to the PhoR start codon) to position 168 was amplified
using CB15N genomic DNA as template and the primers PhoRintupstream for and
PhoRint upstreamrev, and a region from 147 to 1416 was amplified using pENTRCCPhoR(TV) as template and the primers PhoRint_for and PhoRint_rev. Primer
sequences are listed in Table 3.2. The two amplicons were then fused using SOE-PCR
and ligated into pNPTS138, which had been cut with EcoRV and phosphatased using
SAP, to create pNPTS-CCPhoR(TV). This plasmid was used for allelic replacement in
CB 15N following procedures described previously (Skerker et al., 2005). Integrants were
tested for kanamycin sensitivity, sucrose resistance, and sequence-verified using primers
listed in table S8. To create ML1935, PhoR(TV)/AntrX, a tetracycline-marked ntrX
deletion was transduced into ML 1934; transductants were verified by PCR.
Strains used for competition assays (ML1936-ML1945) contained either the coding
region for CFP or YFP driven by the xylX promoter. xylX was amplified from CB I 5N
genomic DNA using primers xylXfor and xylX rev, digested with KpnI and Agel and
Capra| 133
ligated into pXCFPN-4 and pXYFPN-4 using the same restriction sites, producing
pXCFPN-4:PI-cfp-xv/X and pXYFPN-4:PxI-yfp-xy/X. The inserts were then amplified
using primers xyl xfp for and xyl xfp rev, digested with Hindll and EcoRI, and ligated
into pNPTS 138 digested with the same enzymes. These vectors, pNPTS 138 :Pxl-cfp-xylX
and pNPTS138:Px 1 -yfp-xylX, were then integrated into the chromosomes of CB13I5N,
AphoR, AntrX, PhoR(TV), and PhoR(TV)/AntrX through transformation and selection on
kanamycin followed by counterselection on sucrose, leading to markerless integrations of
CFP or YFP at the native xyIX locus of each strain.
Table 3.2 Primers
Genome
E. coli MG 1655
V. fischeri ES 114
S. oneidensis MR-I
P. aeruginosa PAOI
B. thai/andensis E264
R. solanacearum
GMI1000
Accession
number
NP_414933.1
YP_205371.1
NP_717171.1
NP_254047.1
YP_443280.1
NP_519655.1
NP419113.1
Forward primer
Reverse primer
CACCTTGGCGAGACGTATTCTGGTC
TTACGCCATTGGCGAAATACG
CACCTTGGCTAGAAGGATCCTTGTTGT
AGAAGATGAAG
CACCTTGTTGACATTCACTGACAGAAAA
TC
CACCTTGGTTGGCAAGACAATCCTCAT
CGTTGATG
CACCTTGCCCAGCAACATTCTC
TTATGATGTTGGAGAGACACGACGAATT
AC
CTATTTGATGCGGGCAACTAGCTC
CACCTTGCCGAGCATATTCTG
TTACTTGATGCGGGCAAGCAAC
TTAGTCGCCAGGCCCGGTGCG
TACTTGATCCGCGCCATCAG
C. crescentus CB15
M. magneticum sp
CACCTTGACTCCCTACGTTTTGGTGGT
CGAAGAC
CACCTTGACCGCCCGCGAGACCGCC
TTACAGACCCGGGCGGATGCG
YP_420733.1
AMB-1
S. meliloti 1021
NP_384621.1
CACCTTGTTGCCGAAGATTGCCGTAGT
TTAAACCTCGGGCTTGGCGCG
YP_352657.1
YP_162899.1
CACCTTGTCGCCCGCCGATCAGCCCG
CTAGCGCACCCGCGCCATCAGTTC
CACCTTGGCCGCTTTACGGCTACTACT
C
CACCCTGAACCGGCGAAAGGCCGT
CTAAAGGACTCTTGCAACCAGCTC
TCAGGCGCTTCCCGCTTCCGCC
C. crescentus
phoR
CC_1742,
ntrY
CACCTTCGGCGTGCTGGTCAACCG
TCATATCATCTCCTCAACGCCA
C. crescentus
CC _1740,
CACCTTGGCCACCGAAGCTCTGAAA
TCATGCTCGGACGTCTCCGGAA
C. crescentus
ntrB
CC_1741,
ntrCAC
CACCTTGAACGCCGCGAGCAAGAAA
TCAAGTGTCCGCCGGCCGCGACAA
C. crescentus
CC_3743,
CACCTTGTTCCGGCTTATGGCGCAACG
C
TCATGAAGCCTCGTAGCTGCGCAGCTG
C
CACCTTGCAACGAGGGATAGTCTGG
TCACTGGTAATGACTGATAGCGCG
CACCAATCTGGTGCTCAACACCGG
TGGCTAATCATGCGAACAAA
R. sphaeroides 2.4.1
Z. mobilis ZM4
C. crescentus
CC_0289,
cenRAC
E. coli
b_3868,
CTAGCGGACGCGGGCCATCAGTTC
ntrCAC
b_0400, phoR
E. coli
Primers for site directed
mutagenesis
Capra 1134
Name
CC PhoR(TV)
Template
Forward primer
Reverse primer
pENTRCC PhoR
CGCACGCCGCTCACCGTGTTGTCCGG
GAAGCCGGACAACACGGTGAGCGGCG
TGCG
CC PhoR(T)
pENTRCC PhoR
CTGCGCACGCCGCTCACCTCGTTGTCC
pENTRCCPhoR
pENTR-
ACGCCGCTCGCCGTGTTGTCCGGCTTC
GAAGCCGGACAACACGGCGAGCGGCG
TTGTCCGGCTACATCGAGACC
GGTCTCGATGTAGCCGGACAA
GTGTTGTCCGGCTACATCGAGACCCTG
CAGGGTCTCGATGTAGCCGGACAACAC
CCPhoR(V)
CCPhoR(Y)
CTTC
GGC
GCCGGACAACGAGGTGAGCGGCGTGC
GCAG
CCPhoR,
PhoR(TV),
PhoR(T)
pENTRCCPhoR
pENTR-
CCPhoR(VY)
CC_NtrXAC
CCNtrX__D13G
CC_NtrX_G20E
CACCTTGAACGCCGCGAGCAAGAAA
TCAAGTGTCCGCCGGCCGCGACAA
CC NtrX
pENTRCC NtrXAC
GTGGATGACGAGGCCGGCATTCGGGA
GACGAGATCCCGAATGCCGGCCTCGTC
ATCCAC
pENTR-
CGGGATCTCGTCGCCGAAATCCTGGAG
CCNtrXAC(
D13G)
pENTR-
CCNtrX_F1071_K108
A
CC_NtrXAC(
TCTCGTC
ATGAA
TTCATCCTCCAGGATTTCGGCGACGAG
ATCCCG
GAGTTCCTCGAAAAGCCGATCGCATCG
TTTTGCTG
A
CAGCAAAAGCCGGTCCGATGCGATCGG
CTTTTCGAGGAACTC
Forward primer
Reverse primer
GCCTCTCGCTTGAATCGGTGAAGCTC
GAAAACGCCTGCGCCGCCCAC
GTGGGCGGCGCAGGCGTTTTCCTGAA
CCGGCGAAAGGCCGT
TCAGGCGCTTCCCGCTTCCGC
CAGCAGGGTACCTAAGTGGGCGTGAG
TGAATTCCT
CAGCAGACCGGTTTAGAGGAGGCCGC
GGCCGG
CAGCAGAAGCTTCTTGGCCGGCGGCTT
GACCT
CAGCAGGAATTCTTAGAGGAGGCCGCG
GCCGG
GCACGTGTGGAAGTCGAGC
CGTTGAAGGACCGAGAAAGG
CTCGCGACACGCACTAAGGC
GGCGCTGTGCTTATGCGAC
D13G,G20E)
Primers for strain construction
Name
Template
CB15N
PhoRint_upstream
f
PhoR int
xylX
xylX xfp
genomic
pENTRCCPhoR(TV
)
CB15N
genomic
pXCFPN4:Pxyrcfp-
xyIX,
NtrX_tet_conf
pXYFPN4: Pxyl-yfp-xylX
AntrX,
PhoR(TV)/
AntrX
PhoRintsequence
genomic
PhoR(TV)
genomic
Expression vectors were built by moving pENTR clones into destination vectors using
the Gateway LR reaction (Invitrogen), and then transformed into BL21 E. coli for
expression and purification. All site-directed mutagenesis was done on pENTR clones
using primers listed in Table 3.2 and sequence-verified.
Capra 1135
Protein purification and phosphotransfer assays
Expression, protein purification, and phosphotransfer experiments were carried out as
described previously (Skerker et al., 2005). Phosphotransfer profiles against all C.
crescentius regulators comprise three gels, which were run in parallel and exposed to the
same phosphorscreen. Gel images were then stitched together for presentation. Profiles
used full-length response regulators except for CC1741 (ntrC), CC1743 (ntrX), and
CC3743 (cenR) for which only receiver domains were used. For time courses of
phosphotransfer in Figure 3.1 C, each PhoB construct contained only the receiver domain.
Growth and competitive fitness assays
Cultures were grown overnight in M2G. Cultures were then diluted to OD600 - 0.025 and
resuspended in either M2G or M5G. Samples were taken every hour and growth rates
calculated 8-14 hours post-dilution to ensure phosphate-limitation of cells grown in M5G.
For more severe phosphate limitation, growth curves were repeated in M8G, which
contains I 0-fold less phosphate. For these experiments, cultures were grown overnight in
M5G and resuspended at an OD600
0.07 in M8G.
For competitive fitness assays, cultures were grown overnight in M2GX, resuspended in
either M2GX or M5GX to an OD 600 of 0.05, and mixed 1:1 with a competitor strain in 10
mL of media in a 150 mL flask. After 9 hours, a sample was taken and fixed using
paraformaldehyde. Cells were then diluted to OD 600 ~ 0.01 in 10 mL of M2GX or
M5GX. After 15 hours, another sample was taken and cells diluted to OD600 ~ 0.05. After
9 hours, another sample was taken and cells diluted to OD600 - 0.01. This growth and
dilution process was repeated until 104 total hours had elapsed. Cultures typically
Capra 1136
remained below OD600 ~ 0.85 at all times. Cells from each sample collected were
immobilized on 1.5% agarose pads made with PBS, and imaged using a Zeiss Axiovert
200 microscope with a 100x objective. Multiple fields of CFP, YFP, and phase images
were taken for each sample. Roughly 500 cells were counted for each time point using a
custom MATLAB script with counts checked manually using ImageJ. Competition
experiments were done once with wild type expressing cfP and mutant expressing yfy,
repeated with fluorescent proteins swapped, and results averaged.
Microarray analysis
Cultures were grown to mid-log phase in M2G and either RNA was harvested or cells
were washed, resuspended in M5G, and grown for 11 hours in phosphate-limited
conditions before RNA was harvested. RNA was extracted, labeled, and hybridized to
custom-designed 8x15K Agilent expression arrays as described previously (Gora et al.,
2010). NtrX-dependent genes were defined as those genes exhibiting at least a 4-fold
decrease in expression in the AntrXstrain compared to wild-type C. crescentus in M2G.
Complete array data are deposited in GEO.
Capra 1137
Acknowledgements
We thank 0. Ashenberg for help with bioinformatics, Y.E. Chen for help with strain
construction, and A. Podgornaia, A. Keating, 0. Ashenberg, and K. Foster for helpful
comments on the manuscript. Sequence analyses were performed on a computer cluster
supported by NSF grant 0821391. M.T.L. is an Early Career Scientist of the Howard
Hughes Medical Institute. This work was supported by an NSF graduate fellowship to
E.J.C and an NSF CAREER award to M.T.L.
Capral 138
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Capra 1141
Chapter 4
Spatial tethering of kinases to their substrates relaxes
evolutionary constraints on specificity
This work was published as Emily J. Capra, Barrett S. Perchuk, Orr Ashenberg, Charlotte A.
Seid, Hana R. Snow, Jeffrey M. Skerker, Michael T. Laub. 2012. Mol Microbiol.
Dec;86(6):1393-403.
EJC and MTL conceived and designed the experiments. EJC performed most of the experiments.
BSP helped with the protein purifications and the profiles shown in figures 4.3, 4.4 and 4.5. CAS,
HRS, and JMS contributed reagents and helped with preliminary experiments. OA and MTL
performed the computational analysis. EJC and MTL wrote the paper.
Capra 1142
Abstract
Signal transduction proteins are often multidomain proteins that arose through the fusion
of previously independent proteins. How such a change in the spatial arrangement of
proteins impacts their evolution and the selective pressures acting on individual residues
is largely unknown. We explored this problem in the context of bacterial two-component
signaling pathways, which typically involve a sensor histidine kinase that specifically
phosphorylates a single cognate response regulator. Although usually found as separate
proteins, these proteins are sometimes fused into a so-called hybrid histidine kinase.
Here, we demonstrate that the isolated kinase domains of hybrid kinases exhibit a
dramatic reduction in phosphotransfer specificity in vitro relative to canonical histidine
kinases. However, hybrid kinases phosphotransfer almost exclusively to their covalently
attached response regulator domain, whose effective concentration exceeds that of all
soluble response regulators. These findings indicate that the fused response regulator in a
hybrid kinase normally prevents detrimental cross-talk between pathways. More
generally, our results shed light on how the spatial properties of signaling pathways can
significantly affect their evolution, with additional implications for the design of
synthetic signaling systems.
Capra 1143
Introduction
Cells can sense and respond to a remarkable diversity of signals and stimuli. This sensory
capability typically involves a limited number of signal transduction protein families that
have expanded through gene duplication. Although the relative ease of duplication and
divergence has enabled cells to dramatically expand their signaling repertoires, the use of
highly related signaling proteins has a significant cost, or risk. Cells must avoid
detrimental cross-talk and ensure the fidelity of information flow through different
signaling pathways. How the specificity of each signaling pathway is determined and
how it evolves following gene duplication events are important problems that remain
incompletely understood.
In bacteria, the dominant fonn of signal transduction is known as two-component
signaling and typically involves a sensor histidine kinase that can autophosphorylate and
then transfer its phosphoryl group to a cognate response regulator, which effects changes
in cellular physiology or behavior (Stock et al., 2000) (Figure 4.lA). Two-component
signaling genes have undergone extensive duplication and horizontal transfer, such that
most species possess tens or hundreds of these pathways (Galperin, 2005). Previous work
has shown that the interaction between a histidine kinase and its cognate response
regulator is highly specific with limited cross-talk between pathways in vivo (Capra et al.,
2012; Fisher et al., 1996; Grimshaw et al., 1998; Laub and Goulian, 2007; Skerker et al.,
2005). This specificity is determined predominantly at the level of molecular recognition
rather than relying on cellular factors such as scaffolds. Consequently, a histidine kinase
preferentially phosphorylates its cognate response regulator in vitro, relative to all other
response regulators (Skerker et al., 2005).
Capra 1144
signal-w
-+ output
I. IG
response regulator
histidine kinase
B
signal-
H
D
D
RD
hybrid histidine kinase
C
H
D
C
-W output
histidine
response regulator
phosphotransferase
canonical:
score > 3.5
HK853
HK
I
RR
residue canonical hybrid
score
score
pair
72-15
1-13
250-16
251-13
251-15
251-19
II
254-19
E00010
8
55-23
74"
73-15
251-19
250-16, 255-19
211 2519
0
1
2
3
-2
-1
adjusted I acor for hybrid kinasas
4
255-19
257-108
258-22
258-23
269-15
272-15
273-15
6.2
3.9
4.2
39
5.3
4.3
4.2
4.1
4.3
4.4
3.5
4.5
2.5
0.4
2.7
2.2
3.3
2.5
1.2
0.9
1.0
0.5
0.2
1.3
Figure 4.1 Amino acid coevolution analysis of hybrid histidine kinases.
(A) Diagram of canonical two-component signaling pathways and (B) phosphorelays, indicating
the conserved domains in each protein. (C) Coevolving residues in cognate pairs of canonical
histidine kinases and response regulators. Residue pairs with adjusted mutual information scores
greater than 3.5 are listed, connected by lines (left), and shown in spacefilling on a structure of
the T. maritima HK853-RR468 complex (right). The only pair in the hybrid kinase alignment with a
score greater than 3.0 is highlighted. For clarity, only the DHp domain of HK853 is shown.
Residue numbers correspond to positions within EnvZ and OmpR (see Figure 4.2A-B). (D)
Histogram of adjusted mutual information scores for all residue pairs in the hybrid histidine kinase
alignment. Arrows indicate the residue pairs scoring higher than 3.5 in the analysis of canonical
two-component proteins, with scores for these pairs in each alignment listed in the table.
Canonical histidine kinases harbor two highly-conserved domains, a dimerization and
histidine phosphotransfer (DHp) domain and a catalytic and ATP binding (CA) domain.
Capra 1145
The DHp domain promotes homodimerization and harbors the histidine that is
autophosphorylated by the CA domain. Response regulators also typically have two
domains, a receiver domain and an output domain. The receiver domain contains a
conserved aspartate that receives a phosphoryl group from the autophosphorylated kinase
while the output domains are variable, but are often DNA-binding domains.
Phosphotransfer relies primarily on an interaction between the DHp domain of the kinase
and the receiver domain of the regulator (Casino et al., 2009). The residues that
determine the specificity of this interaction were identified through analyses of amino
acid coevolution in large sets of cognate kinase-regulator pairs (Capra et al., 2010;
Skerker et al., 2008). These studies pinpointed a small set of strongly coevolving residues
that determine the specificity of two-component signaling proteins and that enable the
rational rewiring of both the kinase and the regulator (Bell et al., 2010; Capra et al., 2010;
Skerker et al., 2008).
The coevolution of specificity-determining residues in two-component signaling proteins
is driven by negative selection against pathway cross-talk following gene duplication
(Capra et al., 2012). The insulation of recently duplicated two-component proteins
requires changes in the residues that govern molecular recognition, such that each
cognate pair of signaling proteins continues interacting while avoiding cross-talk with the
other pathway. In some cases, changes in the specificity residues of other two-component
signaling proteins, that were not recently duplicated, are also necessary to achieve a
system-wide insulation of all pathways in a given cell (Capra et al., 2012).
Capra 1146
A common variant of two-component signaling involves hybrid histidine kinases, in
which a conventional histidine kinase is fused to a receiver domain similar to those found
in soluble response regulators (Figure 4.1 B). Hybrid kinases autophosphorylate and are
thought to transfer the phosphoryl group intramolecularly to their receiver domains. The
phosphoryl group can then be transferred to a histidine phosphotransferase and finally to
a soluble response regulator, completing a phosphorelay. Hybrid histidine kinases are
found in over 50% of all bacterial genomes and nearly 25% of all bacterial histidine
kinases are hybrids (Wuichet et al., 2010). These hybrid kinases likely arise through the
fusion of canonical, co-operonic histidine kinases and response regulators, and may
further expand through gene duplication (Whitworth and Cock, 2009; Zhang and Shi,
2005).
Despite their prevalence, the phosphotransfer properties and specificity of hybrid kinases
are poorly characterized relative to canonical histidine kinases. Here, we investigated the
global phosphotransfer specificity of hybrid histidine kinases. We find that these hybrid
kinases exhibit significantly reduced phosphotransfer specificity when liberated from
their receiver domains. The covalently attached receiver domain thus normally serves as
an intramolecular phosphoacceptor and helps prevent unwanted cross-talk inside cells.
Our data further indicate that, following the duplication of a hybrid kinase, there is
reduced selective pressure to diversify the residues responsible for binding its attached
response regulator domain, in stark contrast to canonical histidine kinases. In sum, we
propose that the spatial arrangement of domains in hybrid histidine kinases strongly
influences the evolution of these proteins with implications for understanding the
Capra 1147
evolution of multi-domain signaling proteins throughout biology and for designing
synthetic circuits.
Capra 1148
Results
Hybrid kinases show reduced amino acid coevolution between kinase
and receiver domains
Analyses of amino acid coevolution using mutual information as a metric have helped
pinpoint the residues that govern protein-protein interaction specificity in two-component
signal transduction systems (Capra et al., 2010; Skerker et al., 2008). These analyses
identified a small set of residues that map to the molecular interface formed during
phosphotransfer (Casino et al., 2009), and were used to guide the rational rewiring of
substrate specificity for the model histidine kinase EnvZ, validating their role in dictating
specificity (Skerker et al., 2008). To assess whether the same residues coevolve in hybrid
histidine kinases, we examined amino acid coevolution in a large set of hybrid kinases.
This analysis was performed on a multiple sequence alignment containing 2681 hybrid
histidine kinases, drawn from a wide phylogenetic range of organisms. This sequence
alignment contained the DIHp and CA domains of each hybrid kinase as well as its
receiver domain, but omitted sensory domains. To measure coevolution we used a mutual
information-based algorithm that helps adjust for phylogenetic and sampling biases in
sequence alignments (Martin et al., 2005). Adjusted MI values were calculated for all
possible pairs of positions within the sequence alignment (Figure 4.1C, 4.2A-D). A
similar analysis for canonical kinase-regulator pairs was used for comparison (Capra et
aL., 2010). The two alignments have similar entropy at each position, facilitating a
comparison of mutual information scores (Figure 4.2E-F).
We focused primarily on residue pairs in which one position corresponds to a site within
the DHp or CA domains and the other to a site within the receiver domain. The overall
Capra 1149
A
EnvZ
RstB
CpxA
HK853
EnvZ
RstB
CpxA
HK853
HK
EnvZ
RstB
CpxA
HK853
230
240
250
1
260
270
280
290
AGVKQLADDRTLLMAGVS3DLRTP
SEQ-------DGYLAEE1IEECNAIIEQFIDYLRTG---QEM
DNINALIASKKQLIDGIAIELRTPL I
SONL--------SAAESAL0 ISQLEALIEELLTYARLDRPQNEL
TALERMMTSQQRLLSDIS3ELRTPI 3LQ3'LRRR----SGESKELE I
AQRLDSMINDLLVMSRNQQ-KNAL
ERLKRIDRMKTEFIANIS ELRTPI I1<A
IYNSLGELDLSTLKEFLEIIISNHLENLLNELLDFSRLERKSLQI
I
300
310
320
330
340
350
360
EVIAAESGYEREIETALYP-GSIEVKMHPLSIKRAV44VVAARYGNGW-----IKVSSGTEPN
HLSEPDLPLWLSTHLADIQAVTPDKTVRIKTLVQG-HYAALDMR--LMERVL
LN LRYCHST-----VETSLLLSGN
VSETIKANQLWSEVLDNAAFEAEQMGKSLTVNFPP-GPWPLYGNPNALESALE IV
LRYSHTK-----IEVGFAVDKD
NREKVDLCDLVESAVNAIKEFASSHNVNVLFESNVPCPVEAYIDPTRIRQVLI
LLN
VKYSKKDAPDKYVKVILDEKDG
PMEMADLNAVLG ---
370
RAWFQVE
RATLIVE
GITITV
380
390
400
P APEQRKH
QPFVRGDSAR--TIS
P IAPENREHI EPFVRLDPSRDRSTG
P SPEDREQI RPFYRTDEARDRESG
GVLI
OmpR
RstA
CpxR
RR468
QFYRVDSSLTYEVPi
PDHAKDRI
10
B
410
420
430
440
450
IVQRIVDNHN LELGTSERGGLSIRAWLPVPVTRAQGTTKEG
IVHSIALAMG VNCDTSELGGARFSFSWPLWHNIPQFTSA
IVETAIQQHR VKAEDSPLGGLRLVIWLPLYKRS
ITKEIVELHGFI
KGS
PKDRAGEDNRQDN
60
70
30
40
50
M GELSICRRL
LAKHDMQVTVEPRGDQAEETILRENPDLVLL M
1 TICRDL
LEMEGFNVIVAHDGEQALDLLDD-SIDLLL
KKNIDTLKAL
LKKEGYEVIEAENGQIALEKLSEFTPDLIV I
DIFTVLKKL
20
MQENY KLLTEQGFQVRSVANAEQMDRLLTRESFHLMV
--- MNTIVFV
--- MNKILLV
-- MSKKVLLV
I
G
LU
I
-O10
RR
MM O
80
OmpR
RstA
CpxR
RR468
C
90
100
110
120
RSQS--NPMPOI KV3AKGEEVDRIVGLEIADDYI PUIPRELLARIRAVLRRQAN
RAKW---SPIVL SLDSDMNHILALEMACDYI
PAVLLARLRLHLRQNEQ
RQTH---QTPVIMIARGSELDRVLGLE LADDYLP EIDELVA8IRAILRRSHW
QEKEEWKRIPVIV
KGGEEDESLALS LARKVM
PSQFIEEVKHLLNE
-MO
00
-
D
M -
I
hybrid HK-RR
so -
a
-
--
25
N
1000
0
residues
200(
56
25
"covarying
-
canonical HK-RR
2M0
00highly conserved residues
-3
0
1
0' 3
4
5
3
4
6
2
6
£
I
02
0
6
-2
-3
-1
0
adjusted Ml score
3
4
1
2
3
4
adjusted MI score
5
5
6
7~
6
i
F
E
3. 0
3.
0
2 5.
CL
2. 5
2.
0*
0e%
51.
il
A
00
1.
5
1. o
0
-
r0.5
Entropy
1.0
1.5
2.0
-
2.5
In the canonical DHp alignment
3.U
**
500*
0.0
0.5
0~
0
Z
S
1.
e
2.
"a
ee
0
0.5
0
.
*.
..
s
O
1.0
1.5
2.0
2.5
Entropy In the canonical RD alignment
3.0
Figure 4.2 Amino acid coevolution analysis of hybrid histidine kinases.
(A) Sequence alignment of three canonical histidine kinases from E. coli (EnvZ, RstB, CpxA) and
one canonical kinase from T. maritima (HK853). Alignment numbering corresponds to HK853.
The alignment only shows the DHp and CA domains. (B) Sequence alignment of the cognate
response regulators for the kinases in panel A. For panels A and B, the residues that strongly
Capra 1150
coevolve and that dictate specificity in canonical two-component signaling proteins are shaded
orange and red. The pair of residues that also strongly coevolved in the hybrid kinases is marked
by arrows above each alignment. Highly conserved residues is all kinases and receiver domains
are shaded grey. (C-D) Histograms of adjusted mutual information scores for residue pairs in the
multiple sequence alignment of (C) 4,375 canonical, cognate kinase-regulator pairs or (D) 2,681
hybrid histidine kinases (see text for details). Insets show tails of each distribution. (E) Scatter plot
of entropy values for each position in the multiple sequence alignment of DHp domains in
canonical and hybrid kinases. (F) Scatter plot of entropy values for each position in the alignment
of receiver domains in canonical and hybrid kinases.
shape of the distribution of adjusted MI values was similar for the canonical kinaseregulator pairs and the hybrid kinase-receiver domain pairs (Figure 4.2C-D). However, the
hybrid kinase distribution did not contain the same long tail seen in the canonical
distribution. There are 12 pairs of amino acids in the canonical kinase-regulator alignment
that have adjusted MI values greater than 3.5, which indicates significant coevolution. In
contrast, in the hybrid kinase-receiver domain alignment, no residue pair had an MI value
greater than 3.5, and only one pair had a value greater than 3.0 (Figure 4. iC).
The scores for residue pairs in the hybrid kinase alignment were not simply reduced
relative to those from the canonical alignment. Of the 12 top-scoring residue pairs from
the canonical kinase-regulator alignment, only 5 were included in the top 12 scoring pairs
from the hybrid kinase alignment. The other 7 had substantially reduced scores, falling
throughout the distribution, although each had a positive score (Figure 4.1 D). This
analysis suggests that hybrid kinases do not exhibit the same extensive amino acid
coevolution between DHp and receiver domains as canonical kinase-regulator pairs.
Hybrid kinases exhibit limited phosphotransfer specificity
To determine whether the reduced coevolution in hybrid kinases translates into a
difference in kinase specificity, we performed phosphotransfer profiling (Skerker et al.,
Capra| 151
2005). In this approach, a histidine kinase is autophosphorylated using [y- 3 2P]ATP and
then systematically tested for phosphotransfer to a large panel of full-length response
regulators or receiver domains, using SDS-PAGE and phosphorimaging. Robust
phosphotransfer typically manifests both with a band corresponding to a phosphorylated
response regulator and, sometimes, with depletion of the radiolabeled kinase band.
We profiled 10 different hybrid kinases from the a-proteobacterium C. crescentus. In
each case we purified an epitope-tagged construct harboring the DHp and CA domains,
but not the receiver domain. We first profiled each kinase against the entire set of
receiver domains from the 27 annotated C. crescentus hybrid kinases, using incubation
times of 15 minutes (Figure 4.3A-B, 4.4). Strikingly, most of the kinases phosphorylated
several of the hybrid kinase receiver domains. In fact, some kinases phosphorylated the
majority of the receiver domains. These profiles stand in sharp contrast to our results with
canonical histidine kinases in which the phosphotransfer profiles were typically
extremely sparse, with kinases phosphorylating a single cognate response regulator
(Skerker et al., 2008; Skerker et al., 2005).
Interestingly, not all of the hybrid histidine kinases phosphorylated their own receiver
domains. For example, the kinase CC0723 phosphorylated the receiver domains of
CC3075 and CC2670, but not its own, even though other hybrid kinases were able to
phosphorylate the CC0723 receiver domain. There were also several cases in which a
hybrid kinase phosphorylated its own receiver domain, but did so more weakly than other
receiver domains. For example, CC3191 phosphorylated the CC0921 receiver domain to
a greater extent than its own (Figure 4.3A, 4.6B). Thus, unlike canonical kinases for
Capra 1 152
A
C. crescentus hybrid receiver domains
('
(~.
()
D 0'4('(4
(4
r.
to- W00044
W
n
W
W
'.4
M M
Ma W0
M
W
r-
4
M
0000000000000000000
(40
Wi
MM
C4)
CC0138
CC2501
Kfift
Irm
AMM
CC3191
C. crescentus hybrid receiver domains
B
W~ac
M MCCMMtoC
OWV
C
4V
COMWI 4C
C
q 0C4 n , o IPcM ICC
1=
COP.MC
oWW1
DI
000
000c~4C
"C
0C
00000000A0000
DC
CMWC
MC
3
V " )
0
2.0
1.0
phosphotransfer
C. crescentuscanonical response regulators
C
-c
*
V
N= 0
~00000:q
Ce4 Ma
"On) Wo~ C tW
I-aCO
WP_ O
Wo
r-mnWWW
L0)Q
,
IMU)G
b
g
C4 It'.i.
W
M
Q
Figure 4.3 Hybrid histidine kinases show reduced phosphotransfer specificity in
vitro.
(A) Phosphotransfer profiles for kinase domains from three C. crescentus hybrid histidine kinases
against all 27 receiver domains from hybrid kinases. (B) Quantification of phosphotransfer profiles
for 10 hybrid kinases against the 27 hybrid kinase receiver domains; for raw profile data, see
Figure 4.4. (C) Quantification of phosphotransfer profiles for 10 hybrid kinases against the 44
soluble C. crescentus response regulators; for raw profile data, see Figure 4.5. For panels B-C,
the ratio of receiver domain or response regulator band intensity to the autophosphorylated
kinase band intensity was calculated and converted to color based on the legend shown. All
phosphotransfer reactions were incubated 15 minutes.
Capra 1153
C. crescentus hybrid receiver domains
0o00
0$
0
0
0000
000
00
000
CC0026
CC0138
CC0723
CC1078
CC2324
CC2501
40
40
CC3075
CC3102
CC3191
CC3191 - I hour
a,
".
*
46qW -
Capra 1154
Figure 4.4 Phosphotransfer profiles against receiver domains.
The kinase domains from 10 different C. crescentus hybrid histidine kinases were each profiled
against the receiver domains from the 27 hybrid kinases in C. crescentus. Each profile involved
15 minute phosphotransfer reaction times except CC3191 which was profiled at 15 minutes and 1
hour.
which the cognate response regulator is usually the kinetically preferred target, hybrid
kinases display a variety of behaviors, and often harbor substantially less specificity.
Next, we profiled each of the 10 hybrid kinases against the entire set of 44 canonical,
soluble response regulators encoded in the C. crescentus genome (Figure 4.3C, 4.5).
Although these profiles were sparser than those performed against the hybrid kinase
receiver domains, there were significant interactions observed with several of response
regulators.
For
instance,
the
kinase
domain
of
CC2501
showed
significant
phosphotransfer to the regulators CheYIV, DivK, and CC3015. There were also several
response regulators that were phosphorylated by multiple hybrid kinases, including
CC0630, CC2576, CC3015, and CC3286. Finally, we noted that two hybrid kinases,
CC0723 and CC2324, showed stronger phosphotransfer to CC0630 than to any of the
hybrid kinase receiver domains, including their own. These profiles reinforce the
conclusion that hybrid kinases exhibit relaxed phosphotransfer specificity and are
fundamentally different in this respect from canonical histidine kinases.
Physical attachment of a receiver domain reduces signaling cross-talk
Although our data demonstrated a reduced specificity of hybrid kinases, these profiles
were performed using kinases that had been physically separated from their receiver
domains. The kinetic preference and phosphotransfer behavior of these liberated kinase
Capra 1155
C. crescentus canonical response regulators
Me).
C4 he
.P Ma4_
CC0026
CCO138
CC0723
CC1078
CC2324
CC2501
CC2670
CC2971
CC3075
CC3102
CC3191
Figure 4.5 Phosphotransfer profiles against response regulators.
The kinase domains from 10 different C. crescentus hybrid histidine kinases were each profiled at
15 minutes against the 44 soluble response regulators in C. crescentus.
domains likely differ substantially from those of full-length hybrid kinases. For example,
although the kinase domain for CCO138 (ShkA) phosphorylated 16 receiver domains and
3 full-length response regulators, previous studies have indicated that ShkA exclusively
phosphorylates its own receiver domain in vivo (Biondi et al., 2006b). Similarly, although
Capra 1156
A
B
CC3191-HK
CC3191-RD
CC3191-HK +
0
RD
0.25
5 15 30
0.5 1
CheYV
CC3191-RD
CC0921-RD
time (min): 0
HK >-
0 0.25 0.5 1
5 15
30
0 0.25 0.5 1
5 15 30
>
C
4,
0
,4
71
HI
H
H
H
HI
H
HI
H
D
A
D
D
D
D
kinase construct:
time (min):
HK >
D
Ile
0
~.
0
.4N
CC0026
CC0138
CC2670
Figure 4.6 Hybrid kinases lacking their receiver domains exhibit cross-talk.
(A) The kinase-only CC3191 was incubated with CC3191 receiver domain in the presence of [y32]ATP and either buffer, HCI, or NaOH. (B) The kinase-only portion of CC3191 was
autophosphorylated and examined for phosphotransfer to the receiver domains of CC0921 and
CC3191, and to the response regulator CheYV, at the time points indicated. (C) Representative
gels showing the time-course of phosphotransfer to CheYV from each kinase construct in shown
in Figure 4.7B. (D) Representative swarm plates for strains expressing various domains of the
three kinases indicated. Quantifications are shown in Figure 4.7D.
Capra 1157
the kinase domain of CC1078 (CckA) showed apparent promiscuity in vitro and
phosphorylated the response regulator PetR, there is no evidence of cross-talk to this
regulator in vivo and CckA does not activate PetR-dependent genes in vivo (Biondi et al.,
2006a). Thus, we propose that the high local concentration of a covalently attached
receiver domain normally allows this domain to outcompete other response regulators for
access to an autophosphorylated kinase domain.
To further probe the effect of covalently attaching a receiver domain to a histidine kinase,
we focused on the hybrid kinase CC3191. We first compared the phosphotransfer
behavior of the CC3191 construct used in Figure 4.3 that harbors the DHp and CA
domains to a construct that also contains the C-terminal receiver domain of CC3191. The
kinase-only construct for CC3191 phosphorylated its own receiver domain in vitro,
although it also phosphorylated the soluble response regulator CheYV at a similar rate
(Figure 4.3A, 4.6B). In contrast, the longer construct containing the C-terminal receiver
domain no longer detectably phosphotransferred to CheYV (Figure 4.6C, 4.7A). This
result demonstrates that the receiver domain in a hybrid kinase normally prevents crosstalk between the kinase domain and other, soluble response regulators.
The suppression of cross-talk provided by a receiver domain could arise through steric
hindrance or because the kinase domain is engaged in intramolecular phosphotransfer. To
determine whether productive phosphotransfer contributes, we first generated a fulllength CC3191 construct in which the phosphoaccepting aspartate (D563) in the receiver
domain was mutated to
alanine.
This construct
exhibited
significantly
more
phosphotransfer to soluble CheYV than the wild-type CC3191 construct, indicating that
engagement of the kinase domain in intramolecular phosphotransfer contributes to the
Capra 158
suppression of cross-talk (Figure 4.7B), although the receiver domain may also prevent
cross-talk, in part, by occluding the binding of other regulators.
To further understand the contribution of a receiver domain to the prevention of crosstalk, we created chimeric hybrid kinases, fusing the kinase domain of CC3191 to a
receiver domain from CheYIV or CC 1182 (soluble response regulators) or from CC0026
or CC2670 (hybrid kinases). In our profiling studies, the liberated kinase domain of
CC3191
had not
detectably
phosphorylated
CheYIV,
and had
only
weakly
phosphorylated CC 1182 and the receiver domain of CC2670, but it had strongly
phosphorylated the receiver domain of CC0026 (Figure 4.3C). To test whether these four
chimeras could phosphotransfer intramolecularly from the CC3191 kinase domain to the
heterologous receiver domain attached, we autophosphorylated each in buffer, acid, or
base (Figure 4.7A). Histidyl-phosphate bonds are sensitive to acid and aspartyl-phosphate
bonds are sensitive to base (Figure 4.6A). The phosphorylation of CC3191 was decreased
in the presence of either acid or base, indicating that it was phosphorylated on both the
histidine and aspartate. In contrast, the phosphorylation of CC3191(D563A) was
primarily acid sensitive. Together, these patterns of acid/base sensitivity indicate that
CC3191 normally autophosphorylates and transfers its phosphoryl group intramolecularly
to its receiver domain.
We observed a similar pattern, consistent with intramolecular phosphotransfer, for the
chimera CC3191-CC0026 and, to a lesser extent, CC3191-CC2670, but not CC3191CheYIV or CC3191-1182. These findings are consistent with our results indicating that
the CC3191 kinase domain alone can phosphorylate its own receiver domain and the
receiver domains of CC0026 and CC2670, but not CC1 182 or CheYIV (Figure 4.3).
Capra 159
A
CC3191CC3191
CC3191CheYIV
CC3191CC1182
CC3191CC0026
CC3191CC3191(D563A)
B
CC3191CC2670
C
0.G
CC3191 construct
1~1
kinase receiver
domain domain
- CC3191
0.4
-
CC3191-CheYV
A
U0.2
0.2
00
10
- CC3191 -CC1 182D
40
30
20
time (min)
50
CC3191-CC3191
60- CC3191-CCO026
D
1.8 -
*vector
M" kinase-only
1.0 -
0kinase-only (H+A)
receiver domain
[ full length (kinase+receiver)
CCO026
CCO138
CC2670
CC3191
Figure 4.7 Hybrid kinases lacking their receiver domains exhibit cross-talk.
(A) Chimeric hybrid kinases were autophosphorylated in the presence of buffer, HCI, or NaOH to
assess whether phosphoryl groups resided on the conserved histidine, aspartate, or both. (B)
Chimeric hybrid kinases were autophosphorylated and then tested for phosphotransfer to soluble
CheYV at the time points indicated. Error bars represent standard deviation from three
independent replicates. Raw gel images are shown in Figure 4.6C. The identity of domains in
each chimeric kinase are listed. (C) Swarm plate assay for strains expressing each of the
CC3191 constructs listed or vector alone. (D) Quantification of swarm sizes for strains expressing
various constructs for each of the four hybrid histidine kinases indicated. Swarm areas were
measured and plotted relative to the empty vector control. Error bars represent standard
deviations from three replicates. Swarm plate images are shown in Figure 4.6D.
These results also indicate that tethering non-cognate receiver domains to a histidine
kinase is not always sufficient to promote phosphotransfer.
Next, we tested whether the four chimeras would phosphorylate, or cross-talk to, soluble
CheYV. All four chimeras showed reduced phosphotransfer to CheYV compared to the
CC3191 kinase-only construct (Figure 4.6C, 4.7B), with the strongest suppression of
Capra 1160
cross-talk occurring with CC3 191 -CC2670 and CC3191 -CC0026, the two chimeras that
also demonstrated the most significant intramolecular phosphotransfer. Only the
CC3191-CC0026 chimera, whose kinase and receiver domains displayed an interaction
similar to that of CC3191-CC3191, both in isolation and when fused, completely
prevented cross talk. Taken together, our results indicate that the receiver domain of a
hybrid histidine kinase plays an important role in reducing, or eliminating, cross-talk with
other response regulators by interacting with, and receiving phosphoryl groups from, the
linked kinase domain.
Hybrid kinases lacking their receiver domains likely cross-talk to other
response regulators in vivo
Previous work has shown that, with only a few exceptions, canonical histidine kinaseresponse regulator pairs are insulated from each other in vivo (Laub and Goulian, 2007;
Skerker et al., 2005) and, importantly, that cross-talk between non-cognate pairs can be
severely detrimental to an organism's fitness (Capra et al., 2012). We have shown here
that many of the hybrid kinases, when separated from their receiver domains, interact
readily with noncognate response regulators in vitro. Thus, we hypothesized that
expressing only the kinase domain of a hybrid histidine kinase might induce cross-talk in
vivo and affect the growth or fitness of cells.
We tested this hypothesis by inducing expression of CC3191 lacking its C-terminal
receiver domain in C. crescentus and assessing cellular growth in swarm plates. Wildtype C. crescentus cells can swim through low-percentage agar, creating a large circular
colony, or swarm; defects in motility, chemotaxis, cell growth, or cell division can affect
swarm size, making this a convenient assay for assessing gross cellular phenotype
Capra 161
(Skerker et al., 2005). We found that cells producing the kinase-only portion of CC3191
produced a small swarm relative to the wild type without affecting growth or
morphology. This observation is consistent with the notion that a kinase-only version of
CC3191 inappropriately phosphotransfers to CheYV in vivo, as it does in vitro (Figure
4.3C). In contrast, cells synthesizing either a full-length construct that contains the
receiver domain or the receiver domain alone did not exhibit significant swarm
phenotypes (Figure 4.7C-D). The phenotype seen with cells expressing the kinase portion
of CC3191 was dependent on autophosphorylation, as cells overexpressing a construct in
which the conserved histidine was mutated to an alanine no longer exhibited a severe
swarm phenotype.
We then tested the effects of overexpressing three other hybrid histidine kinases that we
profiled above: CC0026, CC0138, and CC2670. Like CC3191, these kinases do not
contain transmembrane domains. As with CC3191, overproducing the N-tenninal and
kinase domains of CC0138 and CC2670 led to a small swarm phenotype, whereas
constructs containing both the kinase and receiver domains, or the receiver domain alone,
did not (Figure 4.6D, 4.7D). For the kinase-only constructs of CC0138 and CC2670, the
phenotype was suppressed by substituting the phosphorylatable histidine with an alanine
suggesting that autokinase activity is required for the small swarm phenotype. Unlike
CC0138 and CC2670, cells synthesizing the kinase-only version of CC0026 did not
exhibit a significant swarm phenotype. Notably, however, the kinase domain of CC0026
had not significantly phosphorylated any non-hybrid receiver domains in vitro (Figure
4.3C). Taken together, these data are consistent with the idea that some hybrid kinases
Capra 1162
are promiscuous, but that their attached receiver domains normally help to prevent crosstalk with other response regulators in vivo.
Hybrid histidine kinases are under reduced selective pressure to
diversify
Collectively, our results indicate that hybrid histidine kinases are subject to different
selective pressures than canonical histidine kinases. We previously found that canonical
histidine kinases and response regulators are under strong selective pressure to diversify
their specificity residues following gene duplication, but are otherwise relatively static
(Capra et al., 2012). This diversification of specificity residues post-duplication is critical
to preventing cross-talk and ultimately ensures the system-wide optimization of
phosphotransfer specificity (Capra and Laub, 2012; Capra et al., 2012). Consistently,
inspection of the six key specificity residues (those from a-helix 1 in the DHp domain) in
genome-wide sets of canonical histidine kinases indicates fewer than three identities at
these six positions in most pairwise comparisons (Figure 4.8).
We extracted the corresponding six residues from each of 24 hybrid histidine kinases in
C. crescentus (Figure 4.8). Although there are 27 annotated hybrid kinases that contain
CA and receiver domains, 3 did not have intact DHp domains. Strikingly, many of the 24
hybrid kinases share four, five, or even six identities at these positions with other hybrid
kinases. This similarity does not arise simply because the hybrid kinases duplicated
recently, as pairwise comparisons of the entire DHp and CA domains demonstrated
extensive variability at other sites (Figure 4.2E-F), resulting in significant separation in a
neighbor-joining tree built from those domains (Figure 4.9A).
Capra 1163
C. crescentus hybrid histidine kinases
kinase domain
CC0026
CC0138
CC0652
CC0723
CC0921
CC0934
CC1078
CC1705
CC2324
CC2501
CC2521
CC2632
CC2670
CC2852
CC2874
CC2971
CC2988
CC2993
CC3075
CC3102
CC3191
CC3219
CC3225
CC3623
(ShkA)
(CckA)
receiver domain
NGGVHV
NGGMRL
TAGFAL
NGGLQA
NGGMHA
NGGb4QI
TALRDE
NANGGR
TGHVAA
TAGFEV
NGAIDR
NSGFQL
NGALAA
NGGMEV
TVGADV
NGALSA
NGAMDA
NAGLEV
NGGLQA
NGGLHA
NGGVHL
NGAMDV
AGGSEM
SAAGGR
NTNVRIS
NINLTLT
NLNMAIT
YVNVMM
NINVTMK
NTNVTLE
EAVVRLD
HINTGIS
DLNMAVS
NVNLAIS
HTNVIVH
HINIALQ
HINVLIT
HTNVLMS
DQVLAMS
NNNVLLT
HVNVAIA
NANVLLA
HVNVLFD
NVNVTIQ
NTNIRMS
NTNVAVE
ETVLDTA
HVNALVD
C. crescentus
canonical histidine kinases
CC1063
CC0238
CC0289
CC0530
CC1181
CC1294
CC1305
CC1594
CC2765
CC2932
CC3327
CC1740
CC1742
CC0759
CC0248
CC2482
CC0586
CC1062
CC2755
CC2884
(DivJ)
(PhoR)
(CenK)
(KdpD)
(NtrB)
(NtrY)
(FixL)
(PleC)
NAGFDI
TSSAET
ASGFET
TSMADR
TRFREA
TAGEEV
AAAQRR
STGATT
SVTESQ
TRLEAM
TSALAD
AGGAQL
TPLSER
SANLTG
ATVVRE
NAGFEI
TSGFEQ
NAGFEI
TRAREV
NAGFSV
C. crescentus
response regulators
CC0284
CC0432
CC0437
CC0440
CC0588
CC0591
CC0596
CC0630
CC0744
CC2463
CC2576
CC3015
CC3258
CC3286
CC3471
CC0237
CC0294
CC1182
CC1293
CC1304
CC1595
CC2757
CC2766
CC2931
CC3035
CC3325
CC3743
CC0909
CC1741
CC1743
CC3315
CC0758
CC1150
CC0247
CC1767
CC0612
CC3477
CC0436
CC0597
CC2462
CC1364
CC2249
CC3100
CC3155
(LovR)
(CheYl)
(CheYII)
(CheYIII)
(CheYIV)
(CheYV)
(CheYVI)
(CpdR)
(DivK)
(PhoB)
(KdpE)
(PetR)
(CtrA)
(CenK)
(FlbD)
(NtrC)
(NtrX)
(TacA)
(FixJ)
(SpdR)
(NasT)
(PhyR)
(CheBI)
(CheBII)
(PleD)
ELLEHLS
STMMMAN
QTMLNAT
NPISQVT
DAILGVE
YTTIGLS
SVIVRMD
ELVMDMN
DSLFRAH
NLNLDLS
ELVEALS
ELVLDMR
NGFLQIS
DVLIITT
SVIVRVD
DNISLAS
EALLYNS
DGIVDFN
DRVFRGS
DVVDKAE
EQIFPAG
DEAAHGA
DDLGLAH
DRLLEFE
DATTLMH
DSHLSVQ
DDLALAR
LGQVKMV
DSIVQAD
EDILGIK
DTQLAVS
DSASFLS
EQKLLSL
DPLRRAD
DKFRTSN
PFSHRRV
EVIDALQ
STMLAAD
SVVMRWA
IANLAKD
NNMVTMT
NHIIAIT
NATLEHN
NHMLEMT
Capra 1164
Figure 4.8 Genome-wide
signaling proteins.
sets of specificity residues from two-component
The key specificity determining residues, as defined through coevolution analysis of canonical
two-component signaling proteins (Figure 4.1), were extracted from each of the histidine kinases,
response regulators, and hybrid histidine kinases in C. crescentus.
The lack of variability at the sites corresponding to the six key specificity residues in
canonical kinases was also evident in sequence logos for the 24 hybrid and 21 canonical
kinases from C. crescentus (Figure 4.9B). The logo for canonical kinases indicated
relatively low conservation at each specificity position except the first, which may be
constrained due to involvement in autophosphorylation (Capra et al., 2010; Casino et al.,
2010). In contrast, the logo for hybrid kinases indicated higher conservation at each site.
The kinase domains of hybrid histidine kinases are likely under less selective pressure
than
canonical
kinases
to
diversify
following
gene
duplication. The
effective
concentration of the attached receiver domain is high enough to ensure that a hybrid
kinase will transfer its phosphoryl group intramolecularly and not to another regulator or
receiver domain. Hence, after duplication of a hybrid kinase, the residues that bind to the
receiver domain do not need to change to insulate the new proteins from one another, as
occurs in canonical kinases (Figure 4.10). Consistent with this hypothesis, many of the
hybrid histidine kinases in C. crescentus, which were likely derived from a common
ancestral gene through duplication and divergence, had similar specificity residues and
exhibited similar phosphotransfer profiles when liberated from their receiver domains
(Figure 4.3B). One exception to this trend was CC 1078 (CckA), which had a distinct set
of specificity residues relative to the other hybrid kinases and, consequently, had a
Capra 1165
A
CC194 CC2884
CC3327
CC0238
CC0248
CC1294
C028
CC2482
CC1740
CCo6
CC0769
CC1078 C27
CC2 32
CC3226
CC319I
cc 01
CCO586
CC0662CC2324C03
Co,
CC1742
CCO630
CC2766
CC1305
ss l
CC87
Qi U
CC2932
CC2766
specificity residues
Figure 4.9 Specificity residues are conserved among hybrid histidine kinases.
(A) An unrooted neighbor-joining tree of the C. crescentus kinases was built from an alignment of
the DHp domains of all 24 hybrid and 21 canonical histidine kinases from C. crescentus. Hybrid
kinases are labeled in red. (B) Sequence logos for the residues that dictate phosphotransfer
specificity in canonical kinase-regulator pairs. Logos were built from an alignment of the 21
canonical histidine kinases and 44 soluble response regulators (top), and from an alignment of
the 24 hybrid histidine kinases in C. crescentus (bottom).
significantly different phosphotransfer profile. Notably, CckA did not group with the
other hybrid kinases in a tree of Caulobacterkinases (Figure 4.9A) suggesting that CckA
may be relatively ancient and not derived from a recent duplication.
Capra 1166
Discussion
The expansion of existing signaling protein families has enabled cells to rapidly evolve
the ability to sense and response to a wide range of stimuli. In bacteria, two-component
signaling proteins have expanded dramatically, such that most species encode dozens,
and sometimes hundreds, of these proteins. For canonical pathways involving a single
histidine kinase and response regulator, these pathways are exquisitely specific and a
cognate response regulator can outcompete all other non-cognate regulators to receive
phosphoryl groups from a given histidine kinase. Consequently, phosphotransfer profiles
of canonical kinases have demonstrated that each possesses a strong kinetic preference
for its cognate substrate (Skerker et al., 2005). This preference is determined by a small
number of specificity-determining residues in both the kinase and regulator. These
residues must coevolve to maintain a tight, specific interaction between cognate partners,
particularly after a gene duplication event as a means of insulating the new pathways
from one another (Figure 4.10) (Capra et al., 2012).
In contrast to the canonical systems, we demonstrated here that kinase domains of hybrid
kinases typically exhibit relaxed substrate specificity, often phosphorylating soluble
response regulators or other receiver domains as well or better than they phosphorylate
their own receiver domains. A similar observation was made previously in Myxococcus
xanthus with a limited set of response regulators. In that case, the kinase domain of RodK
was shown to preferentially phosphorylate the soluble regulator RokA relative to its own
receiver domain, RodK-R3 even though the latter is the in vivo target of RodK (WegenerFeldbrugge and Sogaard-Andersen, 2009).
Capra 1167
&o
canonical histidine kinases
hybrid histidine kinases
HK2
HKHK2
pre-dupication
HK2+
HY1
HK1
ancestral state,
C
HYL
:
Y
gene duplication
HY2
HK3
HK1
O
HK2
K
d.,,.d.
derived state,
post-duplication
H6
1.K3
Figure 4.10 Model for changes in specificity residues following duplication of
canonical and hybrid histidine kinases.
Ovals represent niches within sequence space, or the set of response regulators recognized by a
given histidine kinase as determined by its specificity residues. Post-duplication, canonical
kinases separate in sequence space to insulate the two pathways and prevent cross-talk. In
contrast, hybrid kinases do not separate, as the tethered receiver domain effectively insulates the
duplicated kinases against cross-talk.
Although hybrid kinases are more promiscuous on their own, our data indicate that the
covalently attached receiver domain helps to prevent cross-talk with other cytoplasmic
response regulators. The local concentration of an attached receiver domain likely
exceeds the concentration of all soluble response regulators quite significantly.
Consequently, intramolecular phosphotransfer from the kinase domain to the attached
receiver domain will be strongly favored, thereby ensuring minimal cross-talk to other
pathways.
The enforcement of intramolecular phosphotransfer specificity through spatial tethering
of domains likely eliminates selective pressure to diversify the residues in a hybrid kinase
that mediate docking to the receiver domain. Hence, after a hybrid kinase duplicates,
these residues either will not change or will change more rarely through processes such as
Capra 1168
genetic drift (Figure 4.9B). The net result of the reduced rate of change is that for hybrid
kinases in extant organisms, the interfacial residues show substantially reduced
variability compared to the same set of residues in canonical histidine kinases.
The enforcement of phosphotransfer within hybrid kinases has also likely reduced the
need for their kinase and receiver domains to coevolve (Figure 4.1). Mutations that
reduce or weaken the interaction of these domains are probably more easily tolerated
because the domains are spatially tethered. By contrast, with canonical two-component
pathways, the cognate proteins are under strong pressure to coevolve, as a means of
maintaining their interaction and preventing interaction with non-cognate proteins.
However, merely increasing the effective concentration of a receiver domain was not
always sufficient to induce phosphotransfer from a kinase domain (Figure 4.7A)
indicating some requirement for molecular recognition and a proper pairing of interfacial
residues. It may be that the fusion of domains in a hybrid kinase serves primarily to
prevent cross talk, rather than driving phosphotransfer.
Why some two-component pathways involve hybrid histidine kinases instead of
canonical kinases is not clear. Hybrid kinases are often involved in phosphorelays, and
the additional number of components in a phosphorelay may create additional points for
integrating signals (Burbulys et al., 1991). However, not all hybrid kinases necessarily
participate
in phosphorelays. Recent work with the hybrid kinase VirA from
Agrobacterium tumefaciens suggests that the receiver domain binds the response
regulator VirG, somehow stimulating its activity as a transcriptional activator (Wise et
al., 2010). There are also hybrid kinases in some Gram-positive bacteria, such as
Bacteroides thetaiotaomicron, that have DNA-binding domains C-terminal to their
Capra 1169
receiver domains, suggesting that these kinases may directly regulate transcription
(Raghavan and Groisman, 2010). In short, although nearly a quarter of all kinases are of
the hybrid variety, our understanding of their functions, properties, and advantages
remains limited.
The notion that spatial proximity can overcome relaxed specificity of signaling proteins is
relevant in all cells. Multi-domain signaling proteins are quite common, particularly in
eukaryotes. Additionally, some signal transduction proteins are spatially constrained
through the action of scaffolds. For example, in the S. cerevisiae pheromone pathway, the
scaffold Ste5 enforces the proximity of three separate MAP kinases, helping to prevent
them from inappropriately phosphorylating other substrates (Choi et al., 1994). This
spatial colocalization may, in turn, have relaxed evolutionary constraints on these MAP
kinases.
Finally, our results suggest that information flow through two-component pathways could
be rationally engineered by fusing together non-cognate kinases and regulators. Such an
arrangement can also prevent unwanted cross-talk with other pathways. Indeed, we
showed here that fusing heterologous receiver domains to a hybrid kinase was, in some
cases, sufficient to allow phosphotransfer and prevent cross-talk with a soluble regulator.
Synthetic scaffolds that bring non-cognate two-component signaling proteins in close
proximity may also be used to promote phosphotransfer or prevent cross-talk. A similar
approach of artificially colocalizing proteins has been applied in metabolic engineering
studies, where enzymes have been tethered together to enhance the synthesis and yield of
desired compounds (Dueber et al., 2009).
Capral 170
In sum, our work has revealed new aspects of signaling protein evolution in bacteria that
will likely inform similar evolutionary studies in other organisms and help guide efforts
to construct synthetic signaling circuits.
Capra 1171
Materials and Methods
Sequence analyses
Histidine kinase and response regulator receiver domains were identified, aligned, and
filtered as described previously (Capra et al., 2010). Hybrid kinases were defined as those
proteins that had a single match to each of the three Pfam models: HisKA, HATPaseC,
and Response reg. The final alignment included 2681 hybrid kinases. Shannon entropy
values were calculated for each position in the alignment. Mutual information for every
pair of columns in the sequence alignment was calculated as previously reported (Capra
et al., 2010). Sequence logos were built using WebLogo (weblogo.berkeley.edu).
Neighbor-joining trees were built using the PHYLIP package and multiple sequence
alignments built from the DHp domain of each canonical and hybrid histidine kinase in
the C. crescentus genome.
Strain construction and growth conditions
E. coli and C. crescentus strains were grown as described previously (Skerker et al.,
2005). Primers used are listed in Table 4.1. Full-length hybrid kinases and the kinase
domains of hybrid kinases were amplified from genomic CB15N DNA and ligated into
the Gateway pENTR vector (Invitrogen). Chimeric hybrid kinases were cloned by
separately amplifying the kinase domain from CC3191 and the specified receiver domain,
amplifying the chimeric sequence using splicing with overlap extension PCR and ligating
the resulting product into pENTR. pENTR clones were moved into pDEST-His 6 -MBP or
pDEST-TRX-His 6 vectors for purification, or the pDEST-P\)l-M2 vector derived from
Capral 172
pJS71 for overexpression studies. Overexpression vectors were introduced into wild-type
CB15N via electroporation.
Table 4.1 Primers
Histidine Kinases
Kinase-only
Forward
Reverse
CC0026
CACCTTGTCCCAGGCGTCGACCCCC
TCAGCTGGTCAGCAGCTCCGAGGTC
CC0723
CACCAAGGCCGCCCAGACCAACGG
TCAGGGGTGTTCGCCGCTGAGCGGT
CC2324
CACCCGCATGTTCCGCCGGCAGCA
TCAGGCGCGGGGCGCCCCGGAGGCC
CC2501
CACCGGCCAGCGCTTGCGCCTCGA
TCAGCCCGCGTCGGCGTCAAGGGGC
CC2670
CACCTTGAGAAGAACGACCGCCCAC
TCAGCGCGCCATCACCTGGCCG
CC2971
CACCTTGGCGCGCTACCAAGGGGTG
TCAGGCCGCCGCCGTCAGCGCG
CC3075
CACCCACCAGCGCGGGGCCTCGCG
TCAGCCCTGCAGGGCGGCGGCGCCG
CC3102
CACCCGCACCATGCGCGCCTCGGC
TCAGCCGTCGAGTTGGGTCACGGCG
CC3191
CACCTTGGGCAAGCGCTTGGATACA
TCACCCGTCGAACAGAGGGCCGTCG
Full-length
Forward
Reverse
CC0026
CACCTTGTCCCAGGCGTCGACCCCC
TTAGGCGACGGCGCAGCGGGGG
CC0138
CACCTTGAGCGACAGCAGATCCGAC
TCAGCCGGCGACCTTGGCTCGC
CC2670
CACCTTGAGAAGAACGACCGCCCAC
TCAGCGCGCCATCACCTGGCCG
CC3191
CACCTTGGGCAAGCGCTTGGATACA
TTAGGAGGCCTTGCGCTGGCGC
Forward
Reverse
CC3191-HK
CACCTTGGGCAAGCGCTTGG
CCCGTCGAACAGAGGGCCGT
CheYIV
ACGGCCCTCTGTTCGACGGG
TTGGGCGCGATGCGAATC
CTAGGACGCCGAACGCACCATC
CC1182
ACGGCCCTCTGTTCGACGGG
TTGGAAAACGTCCAAAACGCCGC
TTACTTGGGCAGATAGTCGTCGGCGC
CC0026
ACGGCCCTCTGTTCGACGGG
TTGAAAGTCCTTGTCGTGGAGGACAATCCAC
TTAGGCGACGGCGCAGCGGG
CC2670
ACGGCCCTCTGTTCGACGGG
TTCAAGGTGCTGCTGGCCGAGGATCAC
TCAGCGCGCCATCACCTGGCC
Chimeras
Capra 173
Site-directed mutagenesis
Forward
CC3191 (D563A)
GACCTGATCCTCATGGCCATCCAGATGCCGGTC
CC0026 (H537A)
TTCCTGGCCAATATGAGTGCCGAAATCCGCACCCCCATG
CC0138 (H23A)
CAGCTGGCGACCCTGAGCGCCGAGTTCCGCACGCCCCTG
CC2670 (H330A)
TTCCTGGCCAATATGAGCGCCGAGATCCGCACGCCTTTG
CC3191 (H275A)
TTCCTGGCCAATATGAGCGCCGAGATCCGGACGCCCATG
Protein purification and phosphotransfer assays
Expression, protein purification, and phosphotransfer profiling experiments were carried
out as described previously (Biondi et al., 2006a; Capra et al., 2012; Skerker et al., 2008;
Skerker et al., 2005). All reactions used 500 [M ATP, and 0.5 [Ci/tL [y-
32 P]ATP.
For
phosphotransfer experiments in Figure 4.7A, CC3191 -HK was autophosphorylated under
the same conditions as the phosphotransfer profiles and then incubated with the given
receiver domain in a 1:1 ratio for the time indicated. For phosphotransfer experiments in
Figure 4.7C, 2.5 [M of the specified kinase was mixed with 2.5 [M CheYV before ATP
was added the reaction allowed to proceed for the indicated time before being stopped
with the addition of 4X loading buffer. To test acid or base stability of phosphoryl
groups, 5 iM of kinase was autophosphorylated at room temperature for 15 minutes. The
reaction was then stopped by the addition of 4X loading buffer, and then buffer, 1 M HCI
or 0.5 M NaOH was added. After 20 minutes, reactions were neutralized. All
phosphotransfer experiments were analyzed by SDS-PAGE and phosphorimaging.
Capra 1174
Acknowledgements
We thank Anna Podgornaia for helpful comments on the experiments and on the
manuscript. This work was supported by an NSF CAREER award to MTL and an NSF
GRFP award to EJC. MTL is an Early Career Investigator at the Howard Hughes Medical
Institute.
Capra 1175
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Capra 1177
Chapter 5
Conclusions and future directions
Capral 178
Conclusions
In this work I use bacterial two-component signal transduction pathways to investigate
the evolution of protein-protein interactions between signaling proteins and explore the
mechanisms by which cells can expand their signaling repertoires via duplication and
divergence. More specifically I have investigated the molecular mechanisms by which
two-component pathways can become insulated at the level of signal transduction and
identified selective pressures that act on the kinase/regulator interaction.
Previous work has shown that the interaction between kinase and regulator is incredibly
specific, with most histidine kinases phosphorylating only a single, cognate, response
regulator (Skerker et al., 2008; Skerker et al., 2005). This specificity is mediated through
molecular recognition and determined by a limited set of residues on the kinase and
regulator (Bell et al., 2010; Casino et al., 2009; Skerker et al., 2008). Focusing on this set
of residues that dictate partnering specificity, I showed that the evolutionary trajectory
towards insulation of duplicated two-component systems may be constrained by the need
to maintain interaction between cognate kinases and response regulators while, at the
same time, preventing unwanted interactions with the other two-component proteins in
the genome (Chapter 2). Thus, after a duplication, there may only be a few accessible
paths that result in insulation and the ability to successfully create two insulated pathways
may be determined by the other two-component pathways already in the cell.
Furthermore, I demonstrated that the evolution of these specificity residues is driven by
selection against pathway cross-talk following gene duplication and that cross-talk
between pathways leads to a selective disadvantage in vivo (Chapter 3). 1 determined that
is possible to insulate pathways using only a limited number of mutations and that after a
Capra I179
duplication event, changes in the specificity residues of other two-component signaling
proteins already in the genome may be necessary insulate all pathways within a cell
(Chapter 3). This work may help to explain why some two-component pathways appear
to be more easily duplicated or transferred than others.
In Chapter 4, I investigated covalent attachment as an alternative means of enforcing
interaction specificity between a kinase and its cognate receiver domain. Hybrid kinases,
in which the kinase and the receiver domains are covalently attached, represent almost
25% of all sequenced histidine kinases and nearly all eukaryotic histidine kinases, yet
they remain less well understood than canonical pathways.
I employed the same
coevolution approach that had been used in canonical two-component pathways to
identify specificity residues between kinase and receiver domain in hybrid histidine
kinases and showed that there was significantly less coevolution in hybrid kinases. In
hybrid histidine kinases, no changes to the specificity residues are necessary to
accommodate a duplication; the high effective concentration of the covalently attached
response regulator prevents cross-talk with the other cytoplasmic response regulators in
the cell. Thus the covalent attachment of kinase to substrate may allow a two-component
system to more easily integrate itself into the genome via duplication or horizontal gene
transfer by preventing cross-talk with other two-component proteins already in the
genome.
In short, the question of specificity in two-component signal transduction systems can be
reduced to only a few residues that are sufficient to dictate the partnering specificity. The
impressive fidelity in the kinase-substrate interaction observed in these systems is due to
the significant selective disadvantage against cross-talk and the relatively limited number
Capra 1180
of mutations necessary to change the specificity of the kinase/regulator interaction. This
work sheds light on the apparent ease with which two-component signal transduction
systems have expanded to become the dominant signaling system in bacterial genomes
and, more generally, how a small number of gene families, through duplication and
divergence, can be responsible for signal transduction in all organisms.
Future Directions
HPT specificity and expansion
In this work, I investigated the specificity between histidine kinase and response
regulator, and shown that only a few mutations are sufficient to insulate pathways postduplication. Furthermore, in Chapter 4, I demonstrated that covalent attachment of a
receiver domain to the kinase is another mechanism to enforce specificity and that the
kinase specificity residues of hybrid kinases are not under selective pressure to change
after duplication. I proposed that this may allow hybrid histidine kinases to be more
easily duplicated or transferred between genomes. While this is true, it ignores the
downstream
components
of
the
phosphorelay
pathway.
After
transferring
intramolecularly from kinase to receiver domain, the hybrid histidine kinase then
transfers to a histidine phosphotransferase (HPT) and finally to a response regulator
which effects an output (Figure 5.1 A). Although there are no crystal structures of hybrid
histidine kinases, much less ones in complex with a HPT, the crystal structure of the
response regulator SpoOF with the HPT SpoOB (Zapf et al., 2000) shows that the
kinase/regulator specificity residues also map to the interface between response regulator
and HPT (Skerker et al., 2008). If the interaction surface is conserved and the same
Capra 181
B
Signal
A
Hybrid histidine
kinase
= all residues
0.16
Hp=
Memhmine
ATPCA
specificity residues
0.12
ATP
D0
.20.08
RD
L
0.04
Response RD
regulator
c
CC3058
CC3560
CC3162
EnvZ
Histidine
phosphotransferase
A C D E F G H
I
K L M N P
Q
""
R S TV W Y
------------- AILGPPALIDAQAAQSLALVVH----ELATNASKYG----ALSPRLGRLNVSWGFGDAGV-LHLTWR
------------ TRWDGPELFLTPRAAAALSLALH----ELAVNAVRYG----STENGKVEVVWRRTPEGG-FALEWL
DRITLDCQLRDNAGGHAEDRLR
-------------- IDGERLLQVIDILVENALSAG-----RGMIEVRLS---TGQEMPMEMADLNAVLGEVIAAESGYEREIETALYPGSIEVKMHPLSIKRAVArNMVVNAARYGNGWIKVSSGTEPNRAWF
RAE
1....
10 ........
20.
.
..
........
50........60.......
...
CC3058
CC3560
EDAGASVAAPTQR-------------------rF
ETGGE-PAVAPATK----------------e-
CC3162
EnvZ
MA:I
A LAQSVVR ---- TMGGRLIAEANRGAGLTVGFSLPLI---RVNDPLGGVGGQDRSE -----------QVEfDGPGIAPEQRKHLTQPFVRGDSARTTIG t-AIVQRIVDNHNGMLELGTSERGGLSIRAWLPVPVTRAQGTTKE
..
...
90.......100.......110.......120.......130.......140.......150.......160
TLIQSAV------KQLGAR-----IEHIWRPQGLKVRLDL---
,TLIEDVAG----RELG---------------------------
-
--
-
Figure 5.1 Evolution and specificity of HPT domains.
(A) Outline of a traditional phosphorelay pathway. The kinase/receiver domain interaction in the
hybrid kinase was described in chapter 4, however after transferring intramolecularly, in order to
reach the output of the pathway, two additional phosphotransfer steps are necessary: from the
receiver domain of the hybrid kinase to a histidine phosphotransferase (HPT) and then from the
HPT to the final receiver domain. (B) Graph showing the distribution of amino acids in the
specificity residues of canonical histidine kinases compared to the amino acids that comprise the
DHp domain. Within the specificity residues, there is an overrepresentation of small and nonpolar
amino acids and an underrepresentation of large and charged amino acids. Whether this
distributions represents constraints that are due to the interaction between kinase and receiver
domain or constraints that are due to the need for the kinase to autophosphorylate is unknown.
Data are taken from (Podgornaia and Laub, 2013) (C) Sequence alignment of the CA domains of
3 annotated hybrid kinases within the C. crescentus genome that appear to have degenerated
with the E. coli kinase EnvZ. All three have homology to the HATPase_c_2 (CA domain) family
according to PFAM, as well as to the responsereg family (receiver domain). Although the
histidine is conserved, key residues in the CA domain that are important for autophosphorylation
(shaded in gray), and that are conserved in all or most functional kinases are changed or missing.
These degenerated hybrid kinases represent possible HPTs that may have been used to
increase the signaling complexity in response to a large scale lineage specific expansion of
hybrid kinases in Caulobacter.
Capra 1182
specificity residues are used, what benefit is there to increasing the number of
components in the pathway?
One possibility is that the amino acid composition of specificity residues in canonical
kinases may be constrained. Indeed, certain amino acids are over and under represented
in the specificity residues of canonical histidine kinases (Figure 5.1B) As I showed in
chapter 2, certain substitutions in the specificity residues affect the autophosphorylation
abilities of the kinase. An HPT, however, acts only as a shuttle for phosphate and has no
catalytic abilities of its own. Perhaps using an HPT leads to new and unoccupied
sequence space, defined by specificity residues that prevent autophosphorylation in a
kinase, becoming accessible. Thus the hybrid kinase, whose specificity residues may be
constrained by catalytic function, does not need to evolve new specificity residues in
response to duplication. The HPT, whose specificity residues are unconstrained, can then
find a new, orthogonal and previously unavailable, sequence space.
The second question that the proliferation of hybrid kinases in certain genomes brings up
is where do HPTs come from? There is a defined HPT domain in the PFAM database
based on the structure of the HPT domain from the E. coli hybrid kinase ArcB. However,
almost any protein can act as an HPT as long as there is a histidine within a four helix
bundle. This HPT model fails to identify several characterized HPTs, such as ChpT in
Caulobactercrescentus (Biondi et al., 2006) and HPTs remain difficult to find. In nearly
all cases there are many fewer identifiable HPTs in a genome than hybrid kinases. One
possibility is that duplication of hybrid kinases could be used to create more complex
signaling pathways-i.e. multiple hybrid kinases feed into a single HPT. While this may
Capra 1183
be true in some systems, particularly the Pseudomonasaeruginosavirulence pathway, it
is unlikely to be true in all cases.
One intriguing possibility for the generation of HPTs is that duplicated kinases or hybrid
kinases can degenerate into HPTs. This is probably the origin of the Bacillus sporulation
HPT SpoOB. In C. crescentus, which as I showed in chapter 4 has a large set of recently
duplicated hybrid kinases, 3 of the annotated hybrid kinases are in missing key residues
in the CA domain that are necessary for autophosphorylation (Figure 5.1 C). Each is
cytoplasmic and retains a histidine within an cc-helix. Intriguingly, at least one of these
"hybrid kinases" retains what appears to be an intact receiver domain, indicating that
perhaps it transfers intramolecularly from the HPT to the receiver domain. Further
biochemical assays are necessary to determine whether or not these degenerated hybrid
histidine kinases represent actual HPTs, and whether the receiver domains are indeed
functional.
Explorations of sequence space
In Chapters 2 and 3, I often reference the idea of sequence space in the kinase/regulator
interaction. Experiments from both chapters demonstrate that single mutations in the
specificity residues of either the kinase or the regulator often have little effect on
interaction specificity. However, as also shown in both chapters, certain mutations can
have profound effects. Predicting which mutations will fall into each category aprioriis
currently impossible. Even predicting which kinases will interact with which regulators
purely by sequence has proved challenging, as most methods rely on phylogeny rather
than biochemical principles (Burger and van Nimwegen, 2008; Procaccini et al., 2011).
Capra 1184
There are two approaches that can be taken to begin to answer this question of sequence
space. The first approach is structure based. Currently there is only one structure of a
kinase in complex with its cognate response regulator. Although based on the coevolution
studies and the co-crystal structure of SpoOF and SpoOB (Zapf et al., 2000), the interface
appears to be conserved between kinase/regulator pairs, how a point mutant might affect
the interaction surface remains unclear. In addition, the specificity residues used by
extant two-component systems include a wide range of amino acids. How are different
charges or sizes accommodated along the same interface? What are the biochemical
principles that determine whether or not a kinase will interact with a given response
regulator? By swapping the specificity residues of the Thermotoga maritima twocomponent pair that comprises the co-crystal structure (Casino et al., 2009) with those of
alternative two-component systems, it may be possible to achieve alternative co-crystal
structures that may elucidate the roles of individual point mutations on specificity and
ability to interact, as well as determine how alternate specificity residues might be
accommodated along the same interface.
The second approach is library based. In chapters 2 and 3 of this thesis, I made a large
number of directed mutations and determined whether or not these mutations change
specificity. This approach can be extended to a library based approach, where instead of
introducing each mutation individually, all possible combinations of specificity residues
are introduced into via a single library. An in vivo based screen for kinase/regulator
interaction, such as a fluorescent reporter behind a promoter that is activated by a given
response regulator (Figure 5.2), can then be used to identify the kinases from the library
that preserve the interaction with the cognate response regulator. Illumina sequencing can
Capra 1185
A
A
B
B
Signal
Histidine
kinase
H
H
.
ATP
CA
regulator
:esponsereguiator
Figure 5.2 Library screen to determine sequence space.
(A) The specificity residues of a given kinase (shown in orange) can be replaced with random
amino acids. As the specificity residues are close together in the primary amino acid sequence,
all six important specificity residues can be changed at once. This library of histidine kinases can
be introduced via plasmid and then screened for function. (B) By creating a fluorescent reporter,
the activity of the two-component system can be monitored via microscopy or FACs. Most twocomponent systems autoregulate their own expression, and thus for two-component systems for
which the regulon is unknown, the promotor of the operon containing the histidine kinase and
response regulator can be used for the reporter fusion. Most kinases are bifunctional, and thus in
order to be classified as wild-type, the kinase must be able to activate the promoter in response
to a signal and to turn off the reporter in the absence of the signal. Cells that possess a kinase
with these functions can be sorted and the specificity residues of the kinase sequenced in order
to determine the sequence space of the kinase/regulator pair.
then be used to identify all combinations of specificity residues on the kinase that enable
the interaction between kinase and regulator. This high-throughput screen will allow for
the comprehensive definition of sequence space for a kinase/regulator pair. By repeating
this screen using different two-component pairs within a given genome, the questions of
how sequence space is divided between different two-component systems can begin to be
addressed.
Furthermore, by employing the library approach and gaining a comprehensive
understanding of the distribution of specificity space between two-component pairs
within a genome, it may be possible to gain a deeper understanding as to the mechanisms
Capra 1186
by which duplications of two-component systems are accommodated in the genome.
Gene duplication and divergence has been well-studied, and several models have been
proposed to explain the fate of genes post-duplication: (i) nonfunctionalization, where
one of the duplicated copies becomes non-functional due to mutational accumulation, (ii)
neofunctionalization, where one copy is now free to gain a novel function while the other
retains the ancestral function, and (iii) subfunctionalization, where each copy retains a
subset of the ancestral function (Force et al., 1999; He and Zhang, 2005; Kimura and Ota,
1974; Lynch, 2002; Lynch and Conery, 2000; Lynch and Force, 2000).
Two types of subfunctionalization have been defined. The first type, and the original
model, is known as duplication-degeneration-complementation (DDC). In DDC, after a
duplication event, the ancestral function is divided between the two extant copies. This
means, that post-duplication, both copies are required to carry out the same function as
the ancestral copy. The second type of subfunctionalization, which could also be thought
of as a hybrid neo- and subfunctionalization model, is escape from adaptive conflict
(EAC). In EAC, the ancestral gene has two or more functions. However, when the
functions are encoded in the same protein, the protein cannot be optimized for either
function (Hittinger and Carroll, 2007). Duplication and divergence allows the paralogs to
become specialized and to optimize each of the duplicates to become optimized for the
two ancestral functions. In this case, the functions of the two duplicated copies represent
a gain of function over the ancestral copy. While subfunctionalization has been shown to
be more prevalent, the most commonly studied "function" is expression patterns (Force et
al., 1999; Huminiecki and Wolfe, 2004; Lynch and Force, 2000). In multicellular
organisms subfunctionalization is often accomplished through the degeneration of
Capra 1 187
Insulation via neofunctionalization
Ancestral sequence space
Sequence space Immediately
after duplication
Ae.
"
-
U
-
--
-
Insulation via subfunctionallzation
Figure 5.3 Two models for insulation of pathways post-duplication.
The ancestral two-component pair occupies some defined sequence space. Immediately after
duplication, the specificity residues of, and thus the sequence spaces occupied by, the duplicated
kinases are identical. Over time, in order to insulate pathways, the specificity residues diverge
and the sequence spaces become insulated. In the case of neofunctionalization, one twocomponent pair occupies the ancestral sequence space, while the other two-component pair finds
a new, unoccupied, sequence space. In the case of subfunctionalization, the two-duplicated pairs
now occupy a subset of the ancestral sequence space.
promoter elements, leading to differential tissue-specific expression patterns (Force et al.,
1999; McClintock et al., 2002; Prince and Pickett, 2002; Tilmpel et al., 2006).
Groups have found evidence for both subfunctionalization (Conant and Wolfe, 2007;
Tuch et al., 2008; Wapinski et al., 2007b; Wapinski et al., 2010) and neofunctionalization
(He and Zhang, 2005; Kellis et al., 2004; Tirosh and Barkai, 2007; Wapinski et al.,
2007a, b) in regulatory networks of single-celled organisms post-duplication. However,
many of the studies of protein-protein interactions of duplicates were done in
Saccharomyces cerevisiae, where the occurrence of the whole-genome duplication could
change the evolutionary landscape post-duplication (Guan et al., 2007; Tirosh and Barkai,
2007). In addition, the "function" of a gene is not always easy to define. The evolutionary
history of duplicated pathways, where the "function" is the ability to faithfully transmit a
signal, has not yet been studied.
In the context of kinase-regulator interaction, where function is determined by sequence
space
occupied
by
a
given
two-component
system,
neofunctionalization
vs.
Capra 1188
subfunctionalization can be assessed by determining the distribution of ancestral
sequence
space
post-duplication
(Figure
5.3).
Based
upon
the
models,
if
subfunctionalization is more prevalent, it would be expected that the older and more often
duplication two-component pairs would occupy more constrained sequence spaces, as
each duplication would result in a narrowing of the sequence space. Subfunctionalization
may be easier, as the duplicated two-component systems wouldn't have to traverse new
sequence space that may be occupied by other two-component pairs in the genome.
However, the work in chapter 3 showed that it is possible to insulate pathways, even if
insulation involves interacting with other two-component pairs in the genome. It is
unclear, and will remain unknown until sequence space of a genome is mapped, how
narrowly defined a sequence space can be. Is there a limit to the number of times that a
two-component system can duplicate and diverge via subfunctionalization?
Although high-throughput library based approaches are necessary in order to define the
size and shape of sequence space, to accurately access which model of duplication and
divergence occurred in a given duplication event, detailed ancestral reconstructions are
necessary. Ancestral reconstructions rely on maximum likelihood methods to determine
the most likely sequence of the ancestral proteins. As the function investigated is
specificity, reconstructions can be limited to the amino acid content of the specificity
residues. By performing ancestral reconstructions on relatively recent duplications and
testing the phosphotransfer specificity of these proteins via phosphorylation experiments,
it will be possible to determine which model of duplication and divergence has governed
that particular duplication event. Additional questions, including the number and type of
mutations that are necessary to insulate the pathways and how long cross-talk persists in a
Capra 189
duplicated system can also be answered. However, the speed of change in gene content,
the long branch lengths, and hard to resolve phylogenies between species may make true
ancestral reconstruction difficult.
Sequence space in the response regulator/DNA interaction
In this work, I have outlined the mechanisms by which a two-component system can
become insulated at the level of signal transduction from other two-component systems
also in the genome. However, the ultimate purpose of duplication or horizontal gene
transfer of signaling proteins is to expand the signaling capacity of a cell. In order for this
to be achieved, the output response of the signaling pathway has to change after entry
into the genome and specificity, although in this case the specificity refers to the response
regulator/DNA interaction, has to be ensured. Changes in the output response of one or
both response regulators is likely a critical step in the establishment of new functions and
the maintenance of the duplicated copies within the genome. Yet, there have been few
global studies of the DNA binding specificity of response regulators. Very little
understanding of molecular basis by which response regulators gain new targets after
duplication, or even the distribution of DNA binding sites and the specificity of the
response regulator-target gene interaction on a global level exists.
Understanding the specificity of the response regulator-target gene interaction is an
important one, as response regulators control a large variety of bacterial cellular
processes. Although certain response regulators and their regulons are well studied, for
example CtrA in Caulobactercrescentus, many more remain unstudied at a genome-wide
level. Systematic determination of the binding sites for all response regulators in a given
Capra 1190
genome will allow for the exploration of several important questions. First, how many
genes do most response regulators regulate? How much cross-regulation is there at the
output level? For genes with multiple response regulators serving as regulators, do the
response regulators bind to the same place in the promoter, thus constraining the DNAbinding specificities of these response regulators, or do they have separate and
independent binding sites? The second question is the distribution of response
regulator/DNA-binding specificity within a genome. Like in the kinase/regulator
interaction, paralagous response regulators often share a high sequence and structural
homology. How are so many related response regulators able to coexist in the same
genome and activate genes in a specific way? How much information is encoded in the
DNA binding motif of a given response regulator and how similar or different are the
DNA binding motifs of related response regulators?
The difficulty in identifying specific signals for a given two-component system has
prevented the systematic study of the response regulator/DNA interaction. Even in E.
coli, which has perhaps the best-studied set of two-component systems, the signals
responsible for activating many of these systems remains unclear. As most response
regulators are only active after phosphorylation-induced dimerization, it is necessary to
activate the pathway enough to significantly phosphorylate the response regulator in
order to determine DNA-binding preferences. One way to get around this problem is to
look at in vitro rather than in vivo binding (Rajeev et al., 2011). By examining DNAbinding in vitro, the response regulators can all be phosphorylated to similar levels using
Capra 1191
0~
%an~~-0I
Escherichia coil (29 total)
Salmonella enterica (33
total)
Yersinia pestis(24 total)
-Ibrlo
fischeri (25 total)
Shewanella oneidensis(33 total)
Pseudomonas aeruginosa (54 total)
Figure 5.4 Distribution of E. coli response regulators in a set of well-studied yproteobacteria.
A chart showing presence (yellow) or absence (black) of a given E. coli response regulator in the
genomes shown at right. The total number of DNA-binding response regulators in each genome
are also listed. These genomes represent a wide distribution of number types of response
regulators within the y-proteobacteria. Response regulators whose orthologs are absent in E. coli
are not shown. Duplications in species other than E. coli are also not shown on this diagram.
small molecules or the cognate kinases. Several methods exist to interrogate the binding
properties of a DNA-binding protein, including HiTS-FLIP (Nutiu et al., 2011), MITOMI
(Fordyce et al., 2010) and in vitro CHIP-seq. Results from these in vitro methods can be
compared to in vivo CHIP-seq for those two-component systems whose signals are
known.
One way to extend this work is to look at DNA-binding specificities of orthologs and
paralogs, instead of focusing on a single genome. How do the DNA-binding specificities
differ between orthologs? And how do they change after a duplication event? Previous
work into the evolution of the PhoP response regulator regulon has demonstrated that
while the direct targets of PhoP are highly variable across species, the consensus binding
site is remarkably conserved (Perez et al., 2009). Likewise, although members of the
PhoB regulon can, and do, vary, PhoB boxes are conserved across bacteria. However,
Both PhoP and PhoB have been vertically inherited, and neither has undergone
duplication in a lineage in which they have been studied. However, the histories of most
Capra 1192
FFene4 1
/
mF
_
_ncizao
Neofunctionalization
F ne4 |
F
Ancestral
Immediately
post-duplication
Fgene2|-
Subfunctionalization
Figure 5.5 Evolution of transcriptional networks post-duplication.
The evolution of transcriptional networks after duplication of a transcription factor can also be
described using the models of neo and subfunctionalization. In this case, the function refers to the
identity of the target genes. Due to the speed of transcriptional rewiring, it is unlikely that any
response regulator duplication would fall neatly into either category. By focusing on the core set
of genes, however, it may be possible to divide duplications into one category or the other.
DNA-binding response regulators are not so easy to discern, and there is a great deal of
gain and loss even within the y-proteobacteria (Figure 5.4). How do the transcriptional
networks controlled by orthologous response regulators change between species? One
recent study looked at the regulons of OmpR in two different Salmonella strains, S. typhi
and S. typhimurium and found only a small subset of conserved targets between the two
(Perkins et al., 2013). From previous work, it seems as if transcriptional rewiring is rapid,
although a core set of genes are often conserved. By looking at this core set of genes in
Capra 1193
response regulators that have duplicated, it will be possible to determine whether neo- or
subfunctionalization of target genes is more frequent (Figure 5.5).
Extending the analysis of DNA binding specificities of response regulators to multiple
genomes would allow for the following questions to be answered: (1) are the DNA
binding motifs of most orthologous response regulators conserved, (2) are the trends
observed in the E. coli response regulator set in terms of distribution of binding
specificity the same as those observed in other organisms with vastly different numbers
of DNA binding response regulators and (3) what happens to the DNA binding
specificity of a response regulator after a duplication or after entering a genome via
horizontal gene transfer. As only purified response regulators and genomic DNA are
necessary for in vitro methods to ascertain DNA-binding specificities, it should be
relatively simple to obtain a comprehensive data set from multiple species that represent
a wide variety of ecological and phylogenetic niches.
Concluding remarks
Cells have developed a remarkable capacity to sense and interact with their environment.
This impressive complexity is mediated through only a small number of different types of
signaling pathways that have expanded via duplication and divergence. Understanding
how multiple paralagous pathways can coexist in a genome while at the same time
maintaining signaling fidelity is an important question in understanding the evolution of
complexity. How are input/output relationships maintained? How is a new pathway
incorporated into the signaling network of the cell? Is there a limit to the number of
copies of a given type of signaling pathway that can be encoded in a single cell? Bacterial
Capra 1194
two-component systems represent a tractable model for studying the expansion of
signaling proteins and the mechanisms of duplication and divergence employed in order
to generate complexity. In this work I have shown, in at least one case, the evolutionary
pressures that dictate how, and if, a duplicated two-component pair is integrated into the
signaling network of the cell.
In addition, much of the recent work in synthetic biology has focused on building new
signaling pathways. Two-component pathways make appealing targets for synthetic
biology approaches due to the wide range of signals that are sensed by histidine kinases
and the modularity of these systems. However, the interplay between the synthetic
pathways and the naturally occurring signaling pathways has been ignored. I have shown
that the introduction of a new two-component system into a genome can affect the ability
of pre-existing two-component systems to function. In order for a new, synthetic,
pathway to behave as expected it needs to occupy an orthogonal space from the native
pathways. Understanding of the distribution of sequence space will help with the success
of synthetic approaches to biology using two-component systems.
Understanding the mechanisms by which a new signaling pathways can integrate itself
into the signaling network of the cell and allow the cell to respond to novel signals will
help to shed light on the processes by which cells are able to gain complexity and also
help with efforts to engineer new signaling pathways.
Capra 195
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